Jobs Kyiv, ML / AI
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Β· 30 views Β· 0 applications Β· 22d
Principal ML/AI Engineer
Hybrid Remote Β· Poland, Ukraine Β· Product Β· 6 years of experience Β· English - B2Requirements: Experience with Transformer models: BERT, RoBERTa, GPT, T5, LLaMA, Mistral, Falcon, etc. Strong knowledge of Python; experience with PyTorch, TensorFlow, and Hugging Face Transformers. Understanding of modern LLM architectures and...Requirements:
- Experience with Transformer models: BERT, RoBERTa, GPT, T5, LLaMA, Mistral, Falcon, etc.
- Strong knowledge of Python; experience with PyTorch, TensorFlow, and Hugging Face Transformers.
- Understanding of modern LLM architectures and fine-tuning techniques: LoRA, PEFT, Instruction Tuning, RAG.
- Experience with NLP tasks: classification, text generation, machine translation, QA systems, etc.
- Familiarity with evaluation metrics: accuracy, F1, BLEU, perplexity, ROUGE, etc.
- Basic knowledge of statistics and classical machine learning.
- Experience with MLflow, DVC, or similar tools.
- Experience with model containerization (Docker).
- Understanding of CI/CD principles in ML projects.
- Skills in model deployment using FastAPI / Flask / TorchServe / Triton.
- Experience with cloud infrastructure (AWS, GCP, Azure, or local cloud providers).
Bonus: experience with Kubernetes, Airflow, Kubeflow, Ray.
Responsibilities:
- Selecting and configuring modern Transformer/LLM models for company-specific tasks.
Fine-tuning, LoRA tuning, model distillation, and quantization.
- Preparing and processing datasets (including augmentation).
- Deploying models to production and automating pipelines (data β training β inference).
- Monitoring model performance in production, retraining, and optimization.
- Collaborating with Data Engineers and DevOps to build the MLOps infrastructure.
Evaluating model performance using various metrics and analyzing results to identify areas for improvement and optimization.
We offer you:
- Having the capability to create something new and witness your own input.
- You can find confidence in the future here, but rest assured it won't be dull.
- Join a dynamic and expanding community. Our company is experiencing growth and expanding into Europe. Currently, we have offices in Kyiv, and Warsaw and plan to open additional locations in other countries.
- Full-time employment contract.
- Multisport (light).
- Paid vacation, sick leave.
More
Interested in joining our team? We invite you to submit your CV.
<By submitting your CV to LLC βGigaCloudβ, EDRPOU code [39792589] (hereinafter referred to as the βCompanyβ), in response to our vacancy, you consent to the processing of your personal data contained in the CV by the Company in accordance with the Law of Ukraine βOn Personal Data Protectionβ, ISO 27701 Information Privacy Management System, and the provisions of the GDPR>. -
Β· 43 views Β· 5 applications Β· 16d
ML Computer Vision Engineer
Countries of Europe or Ukraine Β· Product Β· 3 years of experience Β· English - B1 Ukrainian Product πΊπ¦Skylum allows millions of photographers to make incredible images. Our award-winning software automates photo editing with the power of AI yet leaves all the creative control in the hands of the artist. Join us on our mission to make photo editing...Skylum allows millions of photographers to make incredible images. Our award-winning software automates photo editing with the power of AI yet leaves all the creative control in the hands of the artist.
Join us on our mission to make photo editing enjoyable, easy, and accessible to anyone. Youβll be developing products with innovative technologies, providing value and inspiration for customers, and getting inspired in return.
Thanks to our incredible team of experts, weβve built a collaborative space where you can constantly develop and grow in a supportive way. At the same time, we believe in the freedom to be creative. Our work schedule is flexible, and we trust you to give your best while we provide you with everything you need to make work hassle-free. Skylum is proud to be a Ukrainian company, and we stand with Ukraine not only with words but with actions. We regularly donate to various organizations to help speed up the Ukrainian victory.
Role Mission:
We are looking for a strong Machine Learning Engineer who can build and improve ML models used in our product. Most of the tasks are related to computer vision and image processing. You will work on both common tasks like segmentation, detection, and classification, as well as more complex problems involving Diffusion Models, LLMs, VLMs, and other custom tasks without ready-made solutions.
You should be able to work independently, move fast, and quickly test new ideas.
What You Will Do
- Build and improve ML models, mostly for computer vision tasks.
- Handle the full ML process: collect and prepare data, train and test models, and improve them step by step.
- Work on both standard and new types of problems.
- Create fast prototypes and help turn successful ones into real products.
- Work closely with other teams to bring your models into the product.
What Weβre Looking For
- 3+ years of real-world experience with ML, including at least 2 years in computer vision.
- Good understanding of how to build ML systems from start to finish.
- Hands-on experience with one or more of these: object detection, segmentation, img2img, generative networks.
- Ability to read, understand, and implement ideas from cutting-edge research papers. You stay current with top conferences (e.g., CVPR, NeurIPS, ICCV) and can turn academic innovations into practical solutions.
- Strong skills in Python and PyTorch.
- Experience optimizing models for efficient inference on local devices (CPU, GPU, NPU), including quantization, pruning, and runtime adaptation.
- Able to work with and explore large datasets.
- Comfortable working on your own and taking full responsibility for your tasks. Experience with prototyping and working in an R&D cycle.
Nice to Have
- Experience in research (PhD, papers, or personal projects).
- Experience training or fine-tuning foundational models (LLMs, VLMs).
- Experience training or fine-tuning diffusion models for specific image generation or enhancement tasks.
- Familiarity with classical image processing techniques.
- Experience with deep learning inference frameworks like ONNX Runtime, OpenVINO, Core ML, or others.
- Strong C++ skills, close to your Python level.
- Enjoy building and testing product ideas quickly.
What we offer:
For personal growth:
- A chance to work with a strong team and a unique opportunity to make substantial contributions to our award-winning photo editing tools;
- An educational allowance to ensure that your skills stay sharp;
- English and German classes to strengthen your capabilities and widen your knowledge.
For comfort:
- A great environment where youβll work with true professionals and amazing colleagues whom youβll call friends quickly;
- The choice of working remotely or in our office space located on Podil, equipped with everything you might need for productive and comfortable work.
For health:
- Medical insurance;
- Twenty-one days of paid sick leave per year;
- Healthy fruit snacks full of vitamins to keep you energized.
For leisure:
- Twenty-one days of paid vacation per year;
- Fun times at our frequent team-building activities.
If you are looking forward to working with true professionals and simply amazing people & product β we are waiting for your CV!
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Β· 9 views Β· 1 application Β· 1d
AI Computer Vision Engineer
Office Work Β· Ukraine (Kyiv) Β· Product Β· 4 years of experience Β· English - None MilTech πͺThe role is based in the Kyiv region, and we will expect you to work full-time in the office. We have a shuttle service from the nearest metro station. What is your Day to Day Mission: Design, develop, and optimize real-time object detection and...The role is based in the Kyiv region, and we will expect you to work full-time in the office. We have a shuttle service from the nearest metro station.
What is your Day to Day Mission:
- Design, develop, and optimize real-time object detection and tracking models for aerial video from UAVs (EO/IR cameras)
- Implement inference pipelines optimized for edge hardware (e.g., NVIDIA Jetson, Orin)
- Conduct model training, testing, benchmarking, and validation in real flight environments
- Integrate AI models into onboard systems
- Collaborate with other software and hardware teams to ensure robust end-to-end performance
Research and apply state-of-the-art deep learning methods in computer vision
What you bring to the team:
- 3+ years of experience in AI/ML, with a strong focus on computer vision
- Proven experience in object detection/tracking using models like YOLO, SSD, or custom CNNs
- Proficiency in Python, C++, PyTorch or TensorFlow
- Experience with real-time video processing and optimization techniques (e.g., TensorRT, ONNX, pruning, quantization)
- Solid understanding of data annotation, augmentation, and training workflows
- Familiarity with embedded/edge AI deployments (e.g., Jetson Xavier, Orin)
- Experience working with aerial/surveillance imagery or geospatial data is a strong plus
Bachelorβs or Masterβs degree in Computer Science, Robotics, or related field
Nice to Have:
- Knowledge of GStreamer, OpenCV, or similar real-time streaming frameworks
- Familiarity with UAVs, drone flight control, or defense technologies
Understanding of object re-identification or multi-target tracking
Why Quantum-Systems:
- We Stand with Ukraine!
- We believe in the power of combined efforts: straightforward tech expertise paired with a customer-centric focus.
- We are industry pioneers who are ambitious, bold, and visionary.
- We push limits, think outside the box, and strive for technological excellence to shape the future of aerial data.
- We promise to be your runway for individual and professional growth.
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Β· 31 views Β· 9 applications Β· 2d
Data Science / LLM Engineer
Spain, Poland, Portugal, Ukraine Β· 4 years of experience Β· English - NoneQuantum is a global technology partner delivering high-end software products that address real-world problems. We advance emerging technologies for outside-the-box solutions. We focus on Machine Learning, Computer Vision, Deep Learning, GIS, MLOps,...Quantum is a global technology partner delivering high-end software products that address real-world problems.
We advance emerging technologies for outside-the-box solutions. We focus on Machine Learning, Computer Vision, Deep Learning, GIS, MLOps, Blockchain, and more.
Here at Quantum, we are dedicated to creating state-of-art solutions that effectively address the pressing issues faced by businesses and the world. To date, our team of exceptional people has already helped many organizations globally attain technological leadership.
We constantly discover new ways to solve never-ending business challenges by adopting new technologies, even when there isnβt yet a best practice. If you share our passion for problem-solving and making an impact, join us and enjoy getting to know our wealth of experience!
About the position
Quantum is expanding the team and has brilliant opportunities for a Senior Data Science / LLM Engineer. The client is a technological research company that utilizes proprietary AI-based analysis and language models to provide comprehensive insights into global stocks in all languages. Our mission is to bridge the knowledge gap in the investment world and empower investors of all types to become βsuper-investors.β
Through our generative AI technology implemented into brokerage platforms and other financial institutionsβ infrastructures, we offer instant fundamental analyses of global stocks alongside bespoke investment strategies, enabling informed investment decisions for millions of investors worldwide.
Must have skills:
- 4+ years of commercial experience as a Data Science Engineer
- Strong knowledge of linear algebra, calculus, statistics, and probability theory
- Knowledge and experience with algorithms and data structures
- 2+ years of experience with LLM and Natural Language Processing-related tasks
- Knowledge of modern DL architectures
- Experience with at least one of the Deep Learning frameworks (Tensorflow, PyTorch)
- Experience with SQL
- Strong knowledge of OOP
- At least an Upper-Intermediate level of English (spoken and written)
Nice to have skills:
- Experience with production ML/DL frameworks (OpenVino, TensorRT, etc.)
- Docker practical experience
- Experience with Cloud Computing Platforms (AWS, GCloud, Azure)
- Participation in Kaggle competitions
Your tasks will include:
- Full-cycle data science projects
- Data analysis and data preparation
- Development of NLP solution and AI-based chatbots
- Developing models and deploying them to production
- Sometimes, this will require the ability to implement methods from scientific papers and apply them to new domains
We offer:
- Delivering high-end software projects that address real-world problems
- Surrounding experts who are ready to move forward professionally
- Professional growth plan and team leader support
- Taking ownership of R&D and socially significant projects
- Participation in worldwide tech conferences and competitions
- Taking part in regular educational activities
- Being a part of a multicultural company with a fun and lighthearted atmosphere
- Working from anywhere with flexible working hours
- Paid vacation and sick leave days
Join Quantum and take a step toward your data-driven future.
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Β· 24 views Β· 1 application Β· 22d
Lead ML/AI Engineer to $7000
Hybrid Remote Β· Ukraine Β· 5 years of experience Β· English - B2For our client, we are looking for a Senior AI/ML Engineerto join an AI project and drive the design, development, and optimization of cutting-edge retrieval-augmented generation (RAG) solutions. This role is ideal for a highly skilled engineer passionate...For our client, we are looking for a Senior AI/ML Engineerto join an AI project and drive the design, development, and optimization of cutting-edge retrieval-augmented generation (RAG) solutions.
This role is ideal for a highly skilled engineer passionate about AI/ML systems, distributed architectures, and vector search technologies. You will play a key role in designing scalable inference stacks, optimizing retrieval pipelines, and integrating modern frameworks into production-grade applications.
Requirements- 5+ years of experience in software engineering, preferably with AI/ML or distributed systems.
- Proven hands-on experience with retrieval-augmented generation (RAG) systems.
- Deep knowledge of OpenSearch, Elasticsearch or similar search engines.
- Strong coding skills in Python.
- Experience with LlamaIndex, LangChain.
- Familiarity with vector databases (Pinecone, Qdrant, FAISS).
- Exposure to LLM fine-tuning, embeddings, semantic search, prompt engineering.
- Background in high-scale systems handling millions of users/queries daily.
- Knowledge of cloud infrastructure (AWS/GCP/Azure) and containerization (Docker, Kubernetes).
- Experience with vector search, embedding pipelines, dense retrieval techniques.
- Strong optimization skills for latency, reliability, and scalability.
- Excellent problem-solving, analytical, and debugging skills.
- Proactive self-starter with ownership mindset.
- Passion for impactful technology aligned with Geniusees mission.
- Bachelors degree in Computer Science or equivalent practical experience.
- English: Upper-Intermediate+.
- Candidates: Ukrainians (in Ukraine or abroad).
Responsibilities- Design, build, and scale production-grade inference stacks for RAG-based applications.
- Develop efficient retrieval pipelines with OpenSearch/vector DBs ensuring high recall & relevance.
- Optimize performance and latency for real-time and batch queries.
- Identify and fix bottlenecks to improve system efficiency and response times.
- Ensure observability, monitoring, and reliability of deployed systems.
- Collaborate with teams to integrate LLMs and retrieval components into applications.
- Evaluate and integrate modern RAG frameworks and tools.
- Mentor team members, support architectural decisions, and uphold engineering excellence.
- Contribute to pre-sales activities (NFR elicitation, solution architecture, risk definition).
- Conduct discovery phases and recommend tools/libraries.
- Lead/support code reviews, POCs, and R&D.
- Interview external candidates and provide ad hoc troubleshooting.
What You Will Get
- Exciting AI startup projects with a modern stack.
- Career development opportunities (regular reviews).
- Professional study support, certifications, and corporate English.
- VIP medical insurance or sports coverage.
- Paid vacation (18 days) and sick leave.
- Flexible working hours (start 8:00 - 11:30).
- Unlimited remote work worldwide + cozy offices in Kyiv & Lviv with Starlink & generator.
- Compensation for coworking (outside Kyiv & Lviv).
- Corporate lunch, team buildings, soft skills clubs.
- Informal and friendly work culture, no micromanagement.
- Own charity fund.
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Β· 69 views Β· 5 applications Β· 25d
AI-Native Engineer. Context Engineering, SDLC Intelligence
Countries of Europe or Ukraine Β· 4 years of experience Β· English - B2Trinetix is looking for a skilled AI-Native Engineer. We are building an AI-native ecosystem that will power both our internal SDLC and the next generation of AI-driven solutions for our clients. Our R&D organization is developing context-aware AI...Trinetix is looking for a skilled AI-Native Engineer.
We are building an AI-native ecosystem that will power both our internal SDLC and the next generation of AI-driven solutions for our clients. Our R&D organization is developing context-aware AI agents, intelligent engineering tools, and graph-based knowledge systems that integrate directly into real development workflows.
This initiative will reshape how software is planned, built, tested, and evolvedβunlocking entirely new capabilities for our teams and our clientsβ product engineering organizations.
Requirements
- Hands-on experience building RAG systems, vector search, or semantic pipelines.
- Familiarity with knowledge graphs (Neo4j, RDF, property graphs, graph DBs).
- Experience working with LLM APIs (OpenAI, Anthropic, Gemini, Llama, etc.).
- Understanding of embeddings, text processing, chunking strategies, and retrieval optimization.
- Experience building developer tooling, internal tools, plugins, or automation.
- Ability to design and prototype systems independently.
Nice-to-Have
- Experience building agentic systems (AutoGen, LangGraph, crewAI, smolagents, function-calling agents, etc.).
- Experience implementing GraphRAG or similar graph-structured retrieval approaches.
- Familiarity with AI-powered SDLC tools (copilots, code intelligence, static analysis via LLM).
- Understanding of software architecture and system design.
- Experience with CI/CD pipelines, DevOps tooling, or platform engineering.
- Ability to create ontologies or domain data models.
- Experience working in R&D would be preferable.
Core Responsibilities
- Designing the core models and abstractions that will underpin our AI-native engineering ecosystem.
- Developing intelligent mechanisms to surface the right information at the right time.
- Creating assistive capabilities that streamline engineering tasks and workflows.
- Driving innovation in how software teams interact with knowledge, context, and automation.
Collaborating across the organization to embed AI into the end-to-end delivery process.
What We Offer
- Opportunity to build a first-of-its-kind AI-native SDLC environment
- Chance to influence engineering workflows across the entire company
- Work within a high-impact, exploratory R&D team
- Competitive compensation and growth opportunities
- Full autonomy to prototype, test, and implement ideas
- Professional training and English/Spanish language classes
- Comprehensive medical insurance
- Mental health support
- Specialized benefits program with compensation for fitness activities, hobbies, pet care, and more
- Flexible working hours
- Inclusive and supportive culture
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Β· 26 views Β· 1 application Β· 21d
Senior ML/Gen AI Engineer
Hybrid Remote Β· Ukraine Β· 4 years of experience Β· English - B2The project is a big enterprise application with a back office and a mobile client. Weβre going to extend its functionality with SmartWatch (WatchOS) and CarPlay applications for which we will also use LLM/Gen AI. You will be part of a cross-functional,...The project is a big enterprise application with a back office and a mobile client. Weβre going to extend its functionality with SmartWatch (WatchOS) and CarPlay applications for which we will also use LLM/Gen AI. You will be part of a cross-functional, cross-geo team of developers, test engineers, UI/UX designers, and architects who will create applications from scratch and integrate them with the back-office API.
Responsibilities:
- Help the team which consists of BA, Designer UI/UX, Architect, Mobile engineers research and find solutions on how to work with a 3rd party LLM
- Help the team use LLM/Gen AI for mobile applications (iOS, Android and smartwatch)
- Provide feedback to development teams on technical, troubleshooting, or operational issues related to LLM/Gen AI
- Implement and integrate retrieval-augmented generation (RAG)and tool-augmented agents
- Engineer and optimize prompts for LLM-based workflows
- Be up-to-date with advancements in LLMs, agent frameworks, and RAG techniques
- Research and propose improvements to model performance, usability, and tuning
- Prototype ideas for intent recognition, query synthesis, analysis, and reasoning
- Collaborate closely with developers and other stakeholders to ensure system alignment with product and business goals
Requirements:
- 5+ years of experience in Machine Learning, Large Language Models and Generative AI.
- Strong expertise with LLMs (e.g., Gemini, GPT-4, T5, Claude, LLaMA) and generative AI techniques.
- Hands-on experience with ML frameworks such as PyTorch and LangChain, and LangGraph.
- Experience with using prompt engineering techniques to adapt LLMs effectively and/or fine-tuning LLMs using APIs.
- Strong grasp of data structures and data transformation processes.
- Experience serving ML models as API services in production environments.
- Strong knowledge of different types of databases (SQL, noSQL, Vector, etc).
At least upper-Intermediate English (comprehensive written and verbal communication)
Nice-to-Have:
- Experience developing AI agents with external tool integration.
- Working with AI agents for Mobile applications
Working during the discovery phase along with BA, UI/UX, Architect, other engineers
What is in for You:
Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, youβll experience an inclusive culture of acceptance and belonging, where youβll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders.
Learning and development. We are committed to your continuous learning and development. Youβll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.
Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, youβll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine whatβs possible and bring new solutions to market. In the process, youβll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.
Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!
High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, youβre placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.
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Β· 23 views Β· 0 applications Β· 14d
MLOps Engineer
Office Work Β· Ukraine (Kyiv) Β· Product Β· 5 years of experience Β· English - A2 MilTech πͺResponsibilities: Own and support core ML infrastructure (MLflow, CVAT, GPU/CPU cloud instances, internal data tools). Assist Data Engineers with deploying and maintaining data pipelines. Act as the primary contact for ML and Data teams on infra-related...Responsibilities:
- Own and support core ML infrastructure (MLflow, CVAT, GPU/CPU cloud instances, internal data tools).
- Assist Data Engineers with deploying and maintaining data pipelines.
- Act as the primary contact for ML and Data teams on infra-related requests.
- Improve reliability and efficiency by adding automation, monitoring, and tooling enhancements.
Must have:
- Knowledge of Python, Terraform, Docker, Linux.
- Hands-on experience with cloud environments (Azure prefered).
- Understanding of the end-to-end ML lifecycle (data β training β evaluation β deployment β monitoring).
Nice to have:
- Familiarity with Kubernetes.
- Experience with FFmpeg or GStreamer for video processing and streaming.
- Experience with model serving frameworks and inference formats (ONNX, TensorRT, OpenVINO, NVIDIA Triton).
- Experience deploying computer vision models, especially to edge/embedded devices (NVIDIA Jetson, Intel platforms, Raspberry Pi).
- ΠΠ°Π΄Π°ΡΠΌΠΎ Π±ΡΠΎΠ½ΡΠ²Π°Π½Π½Ρ Π²ΡΠ΄ ΠΌΠΎΠ±ΡΠ»ΡΠ·Π°ΡΡΡ
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Β· 38 views Β· 3 applications Β· 12d
AI Application Specialist
Ukraine Β· Product Β· 2 years of experience Β· English - B23Shape develops 3D scanners and software solutions that enable dental and hearing professionals to treat more people, more effectively. Our products are market leading innovative solutions that make a real difference in the lives of both patients and...3Shape develops 3D scanners and software solutions that enable dental and hearing professionals to treat more people, more effectively. Our products are market leading innovative solutions that make a real difference in the lives of both patients and dental professionals around the world.
3Shape is headquartered in Copenhagen, with development teams in Denmark, Ukraine, North Macedonia and with a production site in Poland.
We are a global company with presence in Europe, Asia and the Americas. Founded in a year 2000, today, we provide services to customers in over 130 countries. Our growing talent pool of over 2200 employees spans 50 nationalities.
3Shape as an employer is committed to Ukraine. Our UA office was founded in 2006, and we are continuing to grow, hire and take care of our employees even during the war in Ukraine. Among other actions, we support our contractors who are called to the military service, as well as care about our colleaguesβ mental health by implementing different activities.
About the role:
As an AI Application Specialist, you will spearhead the technical execution of 3Shapeβs After Sales AI Strategy, transforming how we support thousands of dental clinics worldwide. You will bridge the gap between business needs and technical implementation, working closely with the AI Business Owner to design and build high-impact solutions. This is a role for a builder who wants a seat at the table. Beyond execution, you can also play an active role in shaping our AI strategy, directly influencing how we adopt and scale next-gen AI paradigms.Your key responsibilities will be:
- AI Integration: Lead the integration of external AI tools, ensuring every solution delivers measurable business impact.
- Agentic Systems: Design, test, and productionize sophisticated chat and voice agents featuring LLM reasoning and TTS integration.
- Scalable Automation: Architect workflows that streamline operations and drive efficiency across the organization.
- End-to-End Ownership: Take full accountability for the lifecycle of a product from initial concept and design to production and maintenance.
- Enablement: Empower internal teams by providing the training needed to maximize the adoption of custom AI solutions.
Your profile
What we are hoping you have/are:
Education & Experience:- 2β4 years of experience in Software Engineering or AI/ML development, with a deep understanding of how to build and maintain scalable systems.
- Proven end-to-end solution ownership. You have a track record of shipping and supporting AI solutions in production.
Technical Skills:
- Agentic AI Stack: Deep hands-on experience with Agentic Systems, prompt engineering, tool-use (function calling), and RAG/knowledge-base integration. Knowledge of MCP server protocols would be a plus.
- Engineering: Strong Python skills (FastAPI/Flask). Experience in other coding languages would be a plus.
- Tooling: Familiarity with CX platforms (Genesys), Data environments (Databricks/Palantir), or Voice synthesis (ElevenLabs) would be a plus.
Being the part of us means:
- Meaningful work that helps to change the future of dentistry
- Work in a unique professional, friendly and supportive environment
- Constant professional growth and development
- A healthy work-life balance
- Comprehensive benefits incl. 24 working days of annual vacation; medical insurance; paid sick leaves and child sick leaves; maternity and paternity leaves etc
- Breakfasts and lunches in the office
- Good working conditions in a comfortable office in UNIT.City
- A parking lot with free spaces for employees
- Occasional business trips to Western Europe
- Opportunity to become a part of the success that 3Shape has created over the past 25 years.
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Β· 49 views Β· 1 application Β· 6d
Machine Learning
Hybrid Remote Β· Ukraine Β· Product Β· 1 year of experience Β· English - B1ΠΡΡΠ·Ρ, Π½Π°ΡΠ°Π·Ρ ΠΌΠΈ Π·Π½Π°Ρ ΠΎΠ΄ΠΈΠΌΠΎΡΡ Ρ ΠΏΠΎΡΡΠΊΡ Data Science/Machine Learning ΠΠ°Ρ ΠΌΠ°ΠΉΠ±ΡΡΠ½ΡΠΉ ΡΡΠ½ΠΊΡΡΠΎΠ½Π°Π»: ΡΠΊΡΡΠ½Π΅ ΡΠ° ΡΠ²ΠΎΡΡΠ°ΡΠ½Π΅ Π²ΠΈΡΡΡΠ΅Π½Π½Ρ Π±ΡΠ·Π½Π΅Ρ-Π·Π°Π²Π΄Π°Π½Ρ Π·Π° Π½Π°ΠΏΡΡΠΌΠΎΠΌ Π°Π½Π°Π»ΡΠ·Ρ Π΄Π°Π½ΠΈΡ Π·Π° Π΄ΠΎΠΏΠΎΠΌΠΎΠ³ΠΎΡ ΠΌΠ΅ΡΠΎΠ΄ΡΠ² ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ Π΄Π»Ρ ΠΎΡΡΠΈΠΌΠ°Π½Π½Ρ ΠΌΠ°ΠΊΡΠΈΠΌΠ°Π»ΡΠ½ΠΎΠ³ΠΎ...ΠΡΡΠ·Ρ, Π½Π°ΡΠ°Π·Ρ ΠΌΠΈ Π·Π½Π°Ρ ΠΎΠ΄ΠΈΠΌΠΎΡΡ Ρ ΠΏΠΎΡΡΠΊΡ Data Science/Machine Learning
ΠΠ°Ρ ΠΌΠ°ΠΉΠ±ΡΡΠ½ΡΠΉ ΡΡΠ½ΠΊΡΡΠΎΠ½Π°Π»:
- ΡΠΊΡΡΠ½Π΅ ΡΠ° ΡΠ²ΠΎΡΡΠ°ΡΠ½Π΅ Π²ΠΈΡΡΡΠ΅Π½Π½Ρ Π±ΡΠ·Π½Π΅Ρ-Π·Π°Π²Π΄Π°Π½Ρ Π·Π° Π½Π°ΠΏΡΡΠΌΠΎΠΌ Π°Π½Π°Π»ΡΠ·Ρ Π΄Π°Π½ΠΈΡ Π·Π° Π΄ΠΎΠΏΠΎΠΌΠΎΠ³ΠΎΡ ΠΌΠ΅ΡΠΎΠ΄ΡΠ² ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ Π΄Π»Ρ ΠΎΡΡΠΈΠΌΠ°Π½Π½Ρ ΠΌΠ°ΠΊΡΠΈΠΌΠ°Π»ΡΠ½ΠΎΠ³ΠΎ Π±ΡΠ·Π½Π΅Ρ-Π΅ΡΠ΅ΠΊΡΡ;
- ΡΠ΅Π³ΡΠ»ΡΡΠ½Π° ΠΊΠΎΠΌΡΠ½ΡΠΊΠ°ΡΡΡ Π· ΡΠ½ΡΠΈΠΌΠΈ ΠΏΡΠ΄ΡΠΎΠ·Π΄ΡΠ»Π°ΠΌΠΈ Π±Π°Π½ΠΊΡ Π΄Π»Ρ ΠΏΠΎΡΡΠ°Π½ΠΎΠ²ΠΊΠΈ Π·Π°Π²Π΄Π°Π½Ρ Π· Π±ΡΠ·Π½Π΅ΡΠΎΠΌ Π½Π° Π±Π°Π·Ρ ΠΏΡΠ΅Π΄ΠΈΠΊΡΠΈΠ²Π½ΠΎΡ Π°Π½Π°Π»ΡΡΠΈΠΊΠΈ Π΄Π»Ρ Π·ΡΠΎΡΡΠ°Π½Π½Ρ ΠΏΡΠΈΠ±ΡΡΠΊΡ Π±Π°Π½ΠΊΡ;
- Π·Π°Π²Π°Π½ΡΠ°ΠΆΠ΅Π½Π½Ρ ΡΠ° ΠΏΡΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠ° Π΄Π°Π½ΠΈΡ Π΄Π»Ρ ΡΠ΅Π°Π»ΡΠ·Π°ΡΡΡ Data Science ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π΄Π»Ρ Π²ΠΈΡΡΡΠ΅Π½Π½Ρ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π½ΠΈΡ Π±ΡΠ·Π½Π΅Ρ Π·Π°Π²Π΄Π°Π½Ρ;
- ΡΠ΅Π°Π»ΡΠ·Π°ΡΡΡ, Π½Π°Π²ΡΠ°Π½Π½Ρ ΡΠ° ΡΠ½ΡΠ΅ΡΠΏΡΠ΅ΡΠ°ΡΡΡ Data Science ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π΄Π»Ρ Π²ΠΈΡΡΡΠ΅Π½Π½Ρ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π½ΠΈΡ Π±ΡΠ·Π½Π΅Ρ Π·Π°Π²Π΄Π°Π½Ρ;
- ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠ° ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ, Π³Π΅Π½Π΅ΡΠ°ΡΡΡ ΡΠ΄Π΅ΠΉ ΡΠΎΠ΄ΠΎ ΡΡ ΠΏΠΎΠ΄Π°Π»ΡΡΠΎΠ³ΠΎ ΠΏΠΎΠ»ΡΠΏΡΠ΅Π½Π½Ρ;
- Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Π½Ρ Π½ΠΎΠ²ΠΈΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ, ΠΌΠ΅ΡΠΎΠ΄ΡΠ² ΡΠ° ΡΠ½ΡΡΡΡΠΌΠ΅Π½ΡΡΠ² Π΄Π»Ρ Data Science.
ΠΠ°Ρ ΠΊΠ°Π½Π΄ΠΈΠ΄Π°Ρ ΠΌΠ°Ρ:
- Π²ΠΈΡΡ ΡΡΠ½Π°Π½ΡΠΎΠ²ΠΎ-Π΅ΠΊΠΎΠ½ΠΎΠΌΡΡΠ½Π°, ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ½Π° Π°Π±ΠΎ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΠΉΠ½ΠΎ-ΡΠ΅Ρ Π½ΡΡΠ½Π° ΠΎΡΠ²ΡΡΡ;
- Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π½Π΅ ΠΌΠ΅Π½ΡΠ΅ 1-Π³ΠΎ ΡΠΎΠΊΡ Π·Π° Π½Π°ΠΏΡΡΠΌΠΎΠΌ Data Science/Machine Learning Π² Π±Π°Π½ΠΊΡΠ²ΡΡΠΊΡΠΉ, ΡΡΠ½Π°Π½ΡΠΎΠ²ΡΠΉ ΡΡΠ΅ΡΡ Π°Π±ΠΎ ΡΡΠ΅ΡΡ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΠΉΠ½ΠΈΡ ΡΠ΅Ρ Π½ΠΎΠ»ΠΎΠ³ΡΠΉ;
- Π΄ΠΎΡΠ²ΡΠ΄ ΠΏΡΠΎΠ³ΡΠ°ΠΌΡΠ²Π°Π½Π½Ρ Π½Π° Python Π½Π΅ ΠΌΠ΅Π½ΡΠ΅ 1-Π³ΠΎ ΡΠΎΠΊΡ;
- Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· SQL Π½Π΅ ΠΌΠ΅Π½ΡΠ΅ 1-Π³ΠΎ ΡΠΎΠΊΡ;
- Π½Π°Π²ΠΈΡΠΊΠΈ ΠΏΡΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠΈ ΡΡΠ·Π½ΠΈΡ ΡΠΈΠΏΡΠ² Π΄Π°Π½ΠΈΡ Π΄Π»Ρ ΠΌΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ;
- Π½Π°Π²ΠΈΡΠΊΠΈ ΠΏΡΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠΈ Π·Π²ΡΡΡΠ² Π΄Π»Ρ ΠΌΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³Ρ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡΠ² ΡΠΎΠ±ΠΎΡΠΈ ΠΌΠΎΠ΄Π΅Π»Ρ;
- Π½Π°Π²ΠΈΡΠΊΠΈ Π½Π°Π²ΡΠ°Π½Π½Ρ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ;
- Π·Π½Π°Π½Π½Ρ Π±Π°Π·ΠΎΠ²ΠΈΡ ΠΌΠ΅ΡΡΠΈΠΊ ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ;
- Π½Π°Π²ΠΈΡΠΊΠΈ ΡΠ½ΡΠ΅ΡΠΏΡΠ΅ΡΠ°ΡΡΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ.
Π Π½Π°ΠΌΠΈ ΠΠΈ ΠΎΡΡΠΈΠΌΡΡΡΠ΅:
- Π³ΡΠ΄Π½ΠΈΠΉ ΡΡΠ²Π΅Π½Ρ Π·Π°ΡΠΎΠ±ΡΡΠ½ΠΎΡ ΠΏΠ»Π°ΡΠΈ, ΡΠΎ Π²ΠΈΠΏΠ»Π°ΡΡΡΡΡΡΡ 2 ΡΠ°Π·ΠΈ Π½Π° ΠΌΡΡΡΡΡ;
- 28 ΠΊΠ°Π»Π΅Π½Π΄Π°ΡΠ½ΠΈΡ Π΄Π½ΡΠ² Π²ΡΠ΄ΠΏΡΡΡΠΊΠΈ, ΠΎΠΏΠ»Π°ΡΡΠ²Π°Π½Ρ Π»ΡΠΊΠ°ΡΠ½ΡΠ½Ρ;
- ΡΠΎΡΡΡΠ½ΠΈΠΉ ΠΏΠ΅ΡΠ΅Π³Π»ΡΠ΄ Π·Π°ΡΠΎΠ±ΡΡΠ½ΠΎΡ ΠΏΠ»Π°ΡΠΈ;
- ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ Π²ΡΠ΄Π΄Π°Π»Π΅Π½ΠΎ;
Π½Π°Π²ΡΠ°Π»ΡΠ½Ρ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΈ, ΡΠ΅ΠΌΡΠ½Π°ΡΠΈ, ΡΡΠ΅Π½ΡΠ½Π³ΠΈ, ΡΠΈΡΠ°ΡΡΠΊΠΈΠΉ ΠΊΠ»ΡΠ±, ΠΊΡΡΡΠΈ Π°Π½Π³Π»ΡΠΉΡΡΠΊΠΎΡ ΠΌΠΎΠ²ΠΈ ΡΠΎΡΠΎ.
ΠΡΠΊΡΡΠΌΠΎ Π·Π° ΠΠ°Ρ ΡΠ½ΡΠ΅ΡΠ΅Ρ Π΄ΠΎ Π½Π°ΡΠΎΡ Π²Π°ΠΊΠ°Π½ΡΡΡ. Π£ ΡΠ°Π·Ρ ΠΏΠΎΠ·ΠΈΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΡΡΡΠ΅Π½Π½Ρ ΠΌΠΈ Π· ΠΠ°ΠΌΠΈ Π·Π²'ΡΠΆΠ΅ΠΌΠΎΡΡ ΠΏΡΠΎΡΡΠ³ΠΎΠΌ 14-ΡΠΈ Π΄Π½ΡΠ². Π―ΠΊΡΠΎ ΠΏΡΠΎΡΡΠ³ΠΎΠΌ ΡΡΠΎΠ³ΠΎ ΡΠ°ΡΡ ΠΠΈ Π½Π΅ ΠΎΡΡΠΈΠΌΠ°ΡΡΠ΅ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Ρ Π½Π° ΠΠ°ΡΠ΅ ΡΠ΅Π·ΡΠΌΠ΅, Π½Π΅ Π·Π°ΡΠΌΡΡΡΠΉΡΠ΅ΡΡ - ΡΠ΅ ΠΎΠ·Π½Π°ΡΠ°Ρ, ΡΠΎ Π·Π°ΡΠ°Π· ΠΌΠΈ Π½Π΅ ΠΌΠΎΠΆΠ΅ΠΌΠΎ Π·Π°ΠΏΡΠΎΠΏΠΎΠ½ΡΠ²Π°ΡΠΈ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π½Ρ Π²Π°ΠΊΠ°Π½ΡΡΡ, Π°Π»Π΅ Π·Π±Π΅ΡΠ΅Π³Π»ΠΈ ΠΠ°ΡΠ΅ ΡΠ΅Π·ΡΠΌΠ΅ Ρ Π½Π°ΡΡΠΉ Π±Π°Π·Ρ ΠΊΠ°Π΄ΡΠΎΠ²ΠΎΠ³ΠΎ ΡΠ΅Π·Π΅ΡΠ²Ρ. Π―ΠΊΡΠΎ Π² ΠΌΠ°ΠΉΠ±ΡΡΠ½ΡΠΎΠΌΡ Π²Π°ΠΊΠ°Π½ΡΡΡ Π·'ΡΠ²ΠΈΡΡΡΡ, ΠΌΠΈ Π·Π°ΠΏΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ ΠΠ°ΠΌ ΡΠΎΠ·Π³Π»ΡΠ½ΡΡΠΈ ΡΡ.
Π¦Π΅ ΠΎΠ³ΠΎΠ»ΠΎΡΠ΅Π½Π½Ρ Π½Π΅ Ρ ΡΠ΅ΠΊΠ»Π°ΠΌΠΎΡ!
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Senior Deep Learning Engineer (Computer Vision)
Office Work Β· Ukraine (Kyiv) Β· Product Β· 5 years of experience Β· English - None Ukrainian Product πΊπ¦Ajax Systems β ΡΠ΅ ΠΌΡΠΆΠ½Π°ΡΠΎΠ΄Π½Π° ΡΠ΅Ρ Π½ΠΎΠ»ΠΎΠ³ΡΡΠ½Π° ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ, Π½Π°ΠΉΠ±ΡΠ»ΡΡΠΈΠΉ Π² ΠΠ²ΡΠΎΠΏΡ ΡΠΎΠ·ΡΠΎΠ±Π½ΠΈΠΊ Ρ Π²ΠΈΡΠΎΠ±Π½ΠΈΠΊ ΡΠΈΡΡΠ΅ΠΌ Π±Π΅Π·ΠΏΠ΅ΠΊΠΈ Ajax ΡΠ· ΠΌΠΎΠΆΠ»ΠΈΠ²ΠΎΡΡΡΠΌΠΈ ΡΠΎΠ·ΡΠΌΠ½ΠΎΠ³ΠΎ Π΄ΠΎΠΌΡ. Π¦Π΅ ΡΡΠ»Π° Π΅ΠΊΠΎΡΠΈΡΡΠ΅ΠΌΠ° Π·Ρ 180 ΠΏΡΠΈΡΡΡΠΎΡΠ², ΠΌΠΎΠ±ΡΠ»ΡΠ½ΠΈΡ Ρ Π΄Π΅ΡΠΊΡΠΎΠΏΠ½ΠΈΡ Π·Π°ΡΡΠΎΡΡΠ½ΠΊΡΠ², ΡΠ΅ΡΠ²Π΅ΡΠ½ΠΎΡ ΡΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠΈ. ΠΠΎΠΆΠ½ΠΎΠ³ΠΎ...Ajax Systems β ΡΠ΅ ΠΌΡΠΆΠ½Π°ΡΠΎΠ΄Π½Π° ΡΠ΅Ρ Π½ΠΎΠ»ΠΎΠ³ΡΡΠ½Π° ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ, Π½Π°ΠΉΠ±ΡΠ»ΡΡΠΈΠΉ Π² ΠΠ²ΡΠΎΠΏΡ ΡΠΎΠ·ΡΠΎΠ±Π½ΠΈΠΊ Ρ Π²ΠΈΡΠΎΠ±Π½ΠΈΠΊ ΡΠΈΡΡΠ΅ΠΌ Π±Π΅Π·ΠΏΠ΅ΠΊΠΈ Ajax ΡΠ· ΠΌΠΎΠΆΠ»ΠΈΠ²ΠΎΡΡΡΠΌΠΈ ΡΠΎΠ·ΡΠΌΠ½ΠΎΠ³ΠΎ Π΄ΠΎΠΌΡ. Π¦Π΅ ΡΡΠ»Π° Π΅ΠΊΠΎΡΠΈΡΡΠ΅ΠΌΠ° Π·Ρ 180 ΠΏΡΠΈΡΡΡΠΎΡΠ², ΠΌΠΎΠ±ΡΠ»ΡΠ½ΠΈΡ Ρ Π΄Π΅ΡΠΊΡΠΎΠΏΠ½ΠΈΡ Π·Π°ΡΡΠΎΡΡΠ½ΠΊΡΠ², ΡΠ΅ΡΠ²Π΅ΡΠ½ΠΎΡ ΡΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠΈ. ΠΠΎΠΆΠ½ΠΎΠ³ΠΎ ΡΠΎΠΊΡ ΠΌΠΈ Π΄Π΅ΠΌΠΎΠ½ΡΡΡΡΡΠΌΠΎ ΠΊΡΠ°ΡΠ½Π΅ Π·ΡΠΎΡΡΠ°Π½Π½Ρ ΡΠΊ Ρ ΡΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΡ ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ, ΡΠ°ΠΊ Ρ Π² ΠΊΡΠ»ΡΠΊΠΎΡΡΡ ΠΊΠΎΡΠΈΡΡΡΠ²Π°ΡΡΠ² Ρ Π²ΡΡΠΎΠΌΡ ΡΠ²ΡΡΡ. ΠΠ°ΡΠ°Π·Ρ Π² ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ Π±ΡΠ»ΡΡΠ΅ 4 100 ΠΏΡΠ°ΡΡΠ²Π½ΠΈΠΊΡΠ². Π Π΄Π°ΡΡΠΈΠΊΠΈ Ajax ΠΎΡ ΠΎΡΠΎΠ½ΡΡΡΡ 4 ΠΌΠ»Π½ ΠΊΠΎΡΠΈΡΡΡΠ²Π°ΡΡΠ² Ρ Π±ΡΠ»ΡΡ Π½ΡΠΆ 187 ΠΊΡΠ°ΡΠ½Π°Ρ ΡΠ²ΡΡΡ.
ΠΠ° ΡΠΎΠ·ΡΠΎΠ±ΠΊΡ ΠΏΡΠΈΡΡΡΠΎΡΠ² Ρ Ajax Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π°Ρ R&D, ΡΠΊΠΈΠΉ ΡΠΊΠ»Π°Π΄Π°ΡΡΡΡΡ Π· ΡΠΎΡΠΈΡΡΠΎΡ Π΄Π΅ΠΏΠ°ΡΡΠ°ΠΌΠ΅Π½ΡΡΠ²: System, Device, Automation ΡΠ° QA.
ΠΡΠΈΡΡΡΠΎΡ Π²ΡΠ΄Π΅ΠΎΡΠΏΠΎΡΡΠ΅ΡΠ΅ΠΆΠ΅Π½Π½Ρ Ajax ΠΏΠΎΡΠ΄Π½ΡΡΡΡ Π·Π°Π»ΡΠ·ΠΎ, ΡΠΎ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π°Ρ Π²ΠΈΠΌΠΎΠ³Π°ΠΌ Π·Π°ΠΊΠΎΠ½Ρ NDAA, ΠΏΠ΅ΡΠ΅Π΄ΠΎΠ²ΠΈΠΉ ΡΠΎΡΡ Ρ Π²Π±ΡΠ΄ΠΎΠ²Π°Π½ΠΈΠΉ ΡΡΡΡΠ½ΠΈΠΉ ΡΠ½ΡΠ΅Π»Π΅ΠΊΡ, ΡΠΎΠ± Π·Π°Π±Π΅Π·ΠΏΠ΅ΡΠΈΡΠΈ Π½Π΅ΠΏΠ΅ΡΠ΅Π²Π΅ΡΡΠ΅Π½ΠΈΠΉ Π΄ΠΎΡΠ²ΡΠ΄ ΠΊΠΎΡΠΈΡΡΡΠ²Π°Π½Π½Ρ. ΠΠ°ΡΠΎΠ»ΠΎΠ΄ΠΆΡΠΉΡΠ΅ΡΡ ΡΡΡΠΊΠΈΠΌ Π·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½Π½ΡΠΌ ΡΠ΄Π΅Π½Ρ Ρ Π²Π½ΠΎΡΡ, Π·ΡΡΡΠ½ΠΎΡ ΠΉ ΡΠ²ΠΈΠ΄ΠΊΠΎΡ Π½Π°Π²ΡΠ³Π°ΡΡΡΡ Π·Π°Π²Π΄ΡΠΊΠΈ ΠΏΡΠΎΠΏΡΡΡΡΠ°ΡΠ½ΡΠΉ ΡΠ΅Ρ Π½ΠΎΠ»ΠΎΠ³ΡΡ ΠΏΠΎΡΠΎΠΊΠΎΠ²ΠΎΠ³ΠΎ ΠΏΠ΅ΡΠ΅Π΄Π°Π²Π°Π½Π½Ρ Π²ΡΠ΄Π΅ΠΎ ΡΠ° Π½Π°ΠΉΠ²ΠΈΡΠΎΠΌΡ ΡΡΠ²Π½Ρ Π·Π°Ρ ΠΈΡΡΡ ΠΏΡΠΈΠ²Π°ΡΠ½ΠΎΡΡΡ.
ΠΠ΅ΠΎΠ±Ρ ΡΠ΄Π½Ρ Π·Π½Π°Π½Π½Ρ ΡΠ° Π½Π°Π²ΠΈΡΠΊΠΈ:
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΈ, ΡΡΠ΅Π½ΡΠ²Π°Π½Π½Ρ ΡΠ° Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Π½Ρ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π³Π»ΠΈΠ±ΠΎΠΊΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ Π²ΡΠ΄ 2 ΡΠΎΠΊΡΠ² (Π½Π°ΠΏΡΡΠΌΠΎΠΊ - ΠΊΠΎΠΌΠΏ'ΡΡΠ΅ΡΠ½ΠΈΠΉ Π·ΡΡ)
- ΠΠ»ΠΈΠ±ΠΎΠΊΠ΅ ΡΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΠΏΠΎΠΏΡΠ»ΡΡΠ½ΠΈΡ Π°ΡΡ ΡΡΠ΅ΠΊΡΡΡ Π·Π³ΠΎΡΡΠΊΠΎΠ²ΠΈΡ ΠΌΠ΅ΡΠ΅ΠΆ ΡΠ° Π΄Π΅ΡΠ΅ΠΊΡΠΎΡΡΠ²
- ΠΡΠ°ΠΊΡΠΈΡΠ½ΠΈΠΉ Π΄ΠΎΡΠ²ΡΠ΄ Ρ Π·Π°Π²Π΄Π°Π½Π½ΡΡ ΠΊΠ»Π°ΡΠΈΡΡΠΊΠ°ΡΡΡ, Π΄Π΅ΡΠ΅ΠΊΡΡΠ²Π°Π½Π½Ρ, ΡΠ΅Π³ΠΌΠ΅Π½ΡΠ°ΡΡΡ ΡΠ° ΡΡΠ΅ΠΊΡΠ½Π³Ρ ΠΎΠ±'ΡΠΊΡΡΠ²
- ΠΠ»ΠΈΠ±ΠΎΠΊΠ΅ ΡΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΠΊΠΎΠ½ΡΠ΅ΠΏΡΡΠ² ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ ΡΠ° Π³Π»ΠΈΠ±ΠΎΠΊΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ
- ΠΠ½Π°Π½Π½Ρ ΠΏΠΎΠΏΡΠ»ΡΡΠ½ΠΈΡ Π°ΡΡ ΡΡΠ΅ΠΊΡΡΡ Π·Π³ΠΎΡΡΠΊΠΎΠ²ΠΈΡ ΠΌΠ΅ΡΠ΅ΠΆ (AlexNet, MobileNet) ΡΠ° Π΄Π΅ΡΠ΅ΠΊΡΠΎΡΡΠ² (YOLO, SSD)
- ΠΠ½Π°Π½Π½Ρ python, numpy, pandas, scikit-learn, opencv, docker, etc
- ΠΡΠ°ΠΊΡΠΈΡΠ½ΠΈΠΉ Π΄ΠΎΡΠ²ΡΠ΄ΠΎ Ρ PyTorch
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ·Π³ΠΎΡΡΠ°Π½Π½Ρ Π³ΠΎΡΠΎΠ²ΠΈΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π½Π° ΠΏΡΠΎΠ΄Π°ΠΊΡΠ΅Π½Ρ
- ΠΠΌΡΠ½Π½Ρ ΠΎΠΏΡΠΈΠΌΡΠ·Π°ΡΡΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π΄Π»Ρ Π²Π±ΡΠ΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌ (pruning, int8 quantization)
ΠΠΎΡΠ²ΡΠ΄ Ρ ΡΠΎΠ·ΠΌΡΡΡΡ Π΄Π°Π½ΠΈΡ , Π· Π³Π»ΠΈΠ±ΠΎΠΊΠΈΠΌ ΡΠΎΠ·ΡΠΌΡΠ½Π½ΡΠΌ, ΡΠΊΡ Π΄Π°Π½Ρ Π½Π΅ΠΎΠ±Ρ ΡΠ΄Π½Ρ Π΄Π»Ρ ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΠΎΡ ML Π·Π°Π΄Π°ΡΡ
ΠΡΠ΄Π΅ ΠΏΠ»ΡΡΠΎΠΌ:
- ΠΠ½Π°Π½Π½Ρ Π‘/C++β ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· ΠΊΠ»Π°ΡΠΈΡΠ½ΠΈΠΌΠΈ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ°ΠΌΠΈ ΠΊΠΎΠΌΠΏ'ΡΡΠ΅ΡΠ½ΠΎΠ³ΠΎ Π·ΠΎΡΡ
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· Cloud Computing (AWS, GCP, MS Azure)
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· Tensorflow/Keras
- ΠΠ½Π°Π½Π½Ρ Π°ΡΡ ΡΡΠ΅ΠΊΡΡΡ NLP ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ (ΡΡΠ°Π½ΡΡΠΎΡΠΌΠ΅ΡΠΈ)
ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· SD, SDXL
Π§ΠΈΠΌ Π±ΡΠ΄Π΅ΡΠ΅ Π·Π°ΠΉΠΌΠ°ΡΠΈΡΡ:
- Π ΠΎΠ·Π²ΠΈΡΠΊΠΎΠΌ Π½Π°ΠΏΡΡΠΌΡ AI Ρ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ
- ΠΡΠ°ΡΡΠ²Π°ΡΠΈΠΌΠ΅ΡΠ΅ Π· ΠΊΠΎΠΌΠ°Π½Π΄ΠΎΡ Π΄Π°ΡΠ° ΡΠ½ΠΆΠ΅Π½Π΅ΡΡΠ² ΡΠ° Π· ΠΊΠΎΠΌΠ°Π½Π΄ΠΎΡ ΡΠΎΠ·ΠΌΡΡΠΊΠΈ
- Π‘ΡΠ²ΠΎΡΠ΅Π½Π½ΡΠΌ, Π·ΠΌΡΠ½ΠΎΡ ΡΠ° ΠΎΠΏΡΠΈΠΌΡΠ·Π°ΡΡΡΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Ρ Tensorflow/PyTorch
- ΠΠ°Π²ΡΠ°Π½Π½ΡΠΌ, ΠΏΡΠ΄Π±ΡΡΠΎΠΌ Π³ΡΠΏΠ΅ΡΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΡΠ², ΠΏΠΎΠ±ΡΠ΄ΠΎΠ²ΠΎΡ ΠΊΠΎΠ½Π²Π΅ΠΉΡΡΡ Π· Π½Π°Π²ΡΠ°Π½Π½Ρ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π· ΡΡΠ·Π½ΠΈΠΌΠΈ Π½Π°Π±ΠΎΡΠ°ΠΌΠΈ Π΄Π°Π½ΠΈΡ (Π΄Π°ΡΠ°ΡΠ΅ΡΠ°ΠΌΠΈ)
- ΠΠΏΡΠΈΠΌΡΠ·Π°ΡΡΡΡ Π³ΠΎΡΠΎΠ²ΠΈΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΏΡΠ΄ Π²Π±ΡΠ΄ΠΎΠ²Π°Π½Ρ Π΄Π΅Π²Π°ΠΉΡΠΈ
- ΠΠ°Π»Π°Π³ΠΎΠ΄ΠΆΠ΅Π½Π½ΡΠΌ ΡΠ° ΠΏΠΎΡΡΠΊΠΎΠΌ ΠΏΠΎΠΌΠΈΠ»ΠΎΠΊ, Π²ΠΈΠΏΡΠ°Π²Π»Π΅Π½Π½ΡΠΌ
- ΠΠ°ΡΠΈΠΌΠ΅ΡΠ΅ Π±Π°Π³Π°ΡΠΎ Π²Π·Π°ΡΠΌΠΎΠ΄ΡΡ Π· Π΄Π°ΡΠ° ΡΠ½ΠΆΠ΅Π½Π΅ΡΠ°ΠΌΠΈ Π΄Π»Ρ Π²ΡΠ΄Π±ΠΎΡΡ Π½Π°ΠΉΠΊΡΠ°ΡΠΈΡ Π΄Π°Π½ΠΈΡ Π΄Π»Ρ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ
ΠΠ°ΠΏΠΈΡΠ°Π½Π½ΡΠΌ ΡΠΊΡΠΈΠΏΡΡΠ² Π°Π²ΡΠΎΠΌΠ°ΡΠΈΠ·Π°ΡΡΡ ΠΏΡΠΎΡΠ΅ΡΡΠ²
ΠΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ:
- ΠΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ ΠΏΡΠΎΠΏΠΎΠ½ΡΠ²Π°ΡΠΈ ΡΠ° ΡΠ΅Π°Π»ΡΠ·ΠΎΠ²ΡΠ²Π°ΡΠΈ Π²Π»Π°ΡΠ½Ρ ΡΠ΄Π΅Ρ, ΡΠΊΡ ΠΌΠ°ΡΡΡ Π²ΠΏΠ»ΠΈΠ² Π½Π° ΠΏΡΠΎΠ΄ΡΠΊΡ Ρ Π²ΠΈΡΠΎΠ±Π½ΠΈΡΡΠ²ΠΎ
- Π ΠΎΠ±ΠΎΡΡ Ρ Π²ΠΌΠΎΡΠΈΠ²ΠΎΠ²Π°Π½ΡΠΉ ΠΊΠΎΠΌΠ°Π½Π΄Ρ ΡΠ° zero bullshit culture
- ΠΠΎΠ½ΠΊΡΡΠ΅Π½ΡΠ½Ρ Π·Π°ΡΠΎΠ±ΡΡΠ½Ρ ΠΏΠ»Π°ΡΡ
- ΠΠ΅Π΄ΠΈΡΠ½Π΅ ΡΡΡΠ°Ρ ΡΠ²Π°Π½Π½Ρ
- ΠΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½Ρ Π°Π½Π³Π»ΡΠΉΡΡΠΊΡ ΠΌΠΎΠ²Ρ
- ΠΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π²Π·ΡΡΠΈ ΡΡΠ°ΡΡΡ Ρ ΠΏΡΠΎΡΠΊΡΡ Π±Π΅ΡΠ°-ΡΠ΅ΡΡΡ ΡΠΈΡΡΠ΅ΠΌ Π±Π΅Π·ΠΏΠ΅ΠΊΠΈ Ajax β ΠΎΡΡΠΈΠΌΠ°Π½Π½Ρ ΡΠ° ΡΠ΅ΡΡΡΠ²Π°Π½Π½Ρ Π½ΠΎΠ²ΠΈΡ Π³Π°Π΄ΠΆΠ΅ΡΡΠ² Π΄ΠΎ ΡΡ ΡΠ΅Π»ΡΠ·Ρ.
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CRM Content Manager
Office Work Β· Ukraine (Kyiv) Β· Product Β· 1 year of experience Β· English - NoneKing Group β ΡΡΡΠ°ΡΠ½Π° ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ Π· ΡΠ½Π½ΠΎΠ²Π°ΡΡΠΉΠ½ΠΈΠΌ ΠΏΡΠ΄Ρ ΠΎΠ΄ΠΎΠΌ Π΄ΠΎ ΠΏΡΠΎΡΡΠ²Π°Π½Π½Ρ Π±ΡΠ΅Π½Π΄ΡΠ². ΠΠΈ ΠΏΡΠ°ΡΡΡΠΌΠΎ Ρ ΡΡΠ΅ΡΡ iGaming ΡΠ° ΠΌΠ°ΡΠΌΠΎ ΡΡΠΈ ΡΡΠΏΡΡΠ½Ρ ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΡ Π±ΡΠ΅Π½Π΄ΠΈ ΠΎΠ½Π»Π°ΠΉΠ½-ΠΊΠ°Π·ΠΈΠ½ΠΎ, Π° ΡΠ°ΠΊΠΎΠΆ Π²Π»Π°ΡΠ½Ρ ΠΏΠ°ΡΡΠ½Π΅ΡΡΡΠΊΡ ΠΌΠ΅ΡΠ΅ΠΆΡ. ΠΠΈ ΠΎΠΏΠ΅ΡΡΡΠΌΠΎ ΡΠΈΡΠ»Π΅Π½Π½ΠΈΠΌΠΈ ΠΏΡΠΎΡΠΊΡΠ°ΠΌΠΈ Π½Π° ΡΠΈΠ½ΠΊΠ°Ρ Π£ΠΊΡΠ°ΡΠ½ΠΈ, ΠΠ²ΡΠΎΠΏΠΈ ΡΠ°...King Group β ΡΡΡΠ°ΡΠ½Π° ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ Π· ΡΠ½Π½ΠΎΠ²Π°ΡΡΠΉΠ½ΠΈΠΌ ΠΏΡΠ΄Ρ ΠΎΠ΄ΠΎΠΌ Π΄ΠΎ ΠΏΡΠΎΡΡΠ²Π°Π½Π½Ρ Π±ΡΠ΅Π½Π΄ΡΠ². ΠΠΈ ΠΏΡΠ°ΡΡΡΠΌΠΎ Ρ ΡΡΠ΅ΡΡ iGaming ΡΠ° ΠΌΠ°ΡΠΌΠΎ ΡΡΠΈ ΡΡΠΏΡΡΠ½Ρ ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΡ Π±ΡΠ΅Π½Π΄ΠΈ ΠΎΠ½Π»Π°ΠΉΠ½-ΠΊΠ°Π·ΠΈΠ½ΠΎ, Π° ΡΠ°ΠΊΠΎΠΆ Π²Π»Π°ΡΠ½Ρ ΠΏΠ°ΡΡΠ½Π΅ΡΡΡΠΊΡ ΠΌΠ΅ΡΠ΅ΠΆΡ. ΠΠΈ ΠΎΠΏΠ΅ΡΡΡΠΌΠΎ ΡΠΈΡΠ»Π΅Π½Π½ΠΈΠΌΠΈ ΠΏΡΠΎΡΠΊΡΠ°ΠΌΠΈ Π½Π° ΡΠΈΠ½ΠΊΠ°Ρ Π£ΠΊΡΠ°ΡΠ½ΠΈ, ΠΠ²ΡΠΎΠΏΠΈ ΡΠ° Π‘Π¨Π, ΡΠ½Π²Π΅ΡΡΡΡΠΌΠΎ Ρ Π²Π΅Π½ΡΡΡΠ½Ρ ΡΡΠ°ΡΡΠ°ΠΏΠΈ, ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Π½Ρ ΡΠ΄Π΅Ρ ΡΠ° Π»ΡΠ΄Π΅ΠΉ.
ΠΠΈ ΡΡΠΊΠ°ΡΠΌΠΎ CRM Content Manager, ΡΠΊΠΈΠΉ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π°ΡΠΈΠΌΠ΅ Π·Π° ΡΠΊΡΡΡΡ, Π»ΠΎΠ³ΡΠΊΡ ΡΠ° ΠΊΠΎΡΠ΅ΠΊΡΠ½ΡΡΡΡ ΠΊΠΎΠ½ΡΠ΅Π½ΡΡ Π² CRM-ΠΊΠΎΠΌΡΠ½ΡΠΊΠ°ΡΡΡΡ : email, push, SMS ΡΠ° in-app.
Π¦Ρ ΡΠΎΠ»Ρ ΡΠ΄Π΅Π°Π»ΡΠ½ΠΎ ΠΏΡΠ΄ΡΠΉΠ΄Π΅ ΡΠΎΠΌΡ, Ρ ΡΠΎ Π»ΡΠ±ΠΈΡΡ ΠΏΠΎΡΡΠ΄ΠΎΠΊ, ΡΡΡΡΠΊΡΡΡΡ, ΡΠ²Π°ΠΆΠ½ΠΈΠΉ Π΄ΠΎ Π΄Π΅ΡΠ°Π»Π΅ΠΉ, Π°Π»Π΅ ΠΏΡΠΈ ΡΡΠΎΠΌΡ Ρ ΠΎΡΠ΅ ΡΠΎΠ·Π²ΠΈΠ²Π°ΡΠΈΡΡ Π² Π½Π°ΠΏΡΡΠΌΠΊΡ CRM Ρ retention.
Π’Π²ΠΎΡ ΠΎΡΠ½ΠΎΠ²Π½Ρ Π·Π°Π΄Π°ΡΡ
β’ ΠΡΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠ°, Π½Π°Π»Π°ΡΡΡΠ²Π°Π½Π½Ρ ΡΠ° Π·Π°ΠΏΡΡΠΊ CRM-ΠΊΠΎΠΌΡΠ½ΡΠΊΠ°ΡΡΠΉ (email, push, SMS).
β’ Π ΠΎΠ±ΠΎΡΠ° Π· Π³ΠΎΡΠΎΠ²ΠΈΠΌΠΈ ΡΠ°Π±Π»ΠΎΠ½Π°ΠΌΠΈ ΡΠ° ΠΊΠΎΠ½ΡΠ΅Π½ΡΠΎΠΌ: Π°Π΄Π°ΠΏΡΠ°ΡΡΡ, Π»ΠΎΠΊΠ°Π»ΡΠ·Π°ΡΡΡ, ΠΏΠ΅ΡΠ΅Π²ΡΡΠΊΠ° Π»ΠΎΠ³ΡΠΊΠΈ ΡΠ° ΠΊΠΎΡΠ΅ΠΊΡΠ½ΠΎΡΡΡ.
β’ ΠΠ°Π»Π°ΡΡΡΠ²Π°Π½Π½Ρ ΠΊΠΎΠ½ΡΠ΅Π½ΡΡ Π² CRM-ΡΠΈΡΡΠ΅ΠΌΡ: Π»Π°Π½ΡΡΠΆΠΊΠΈ, ΡΡΠΈΠ³Π΅ΡΠΈ, ΡΠ°ΠΉΠΌΡΠ½Π³ΠΈ, ΡΠ΅Π³ΠΌΠ΅Π½ΡΠΈ.
β’ ΠΠΎΠ½ΡΡΠΎΠ»Ρ ΡΠΊΠΎΡΡΡ CRM-ΠΊΠ°ΠΌΠΏΠ°Π½ΡΠΉ ΠΏΠ΅ΡΠ΅Π΄ Π·Π°ΠΏΡΡΠΊΠΎΠΌ (ΡΠ΅ΠΊΡΡΠΈ, ΠΏΠΎΡΠΈΠ»Π°Π½Π½Ρ, ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ·Π°ΡΡΡ).
β’ Π£ΡΠ°ΡΡΡ Ρ ΠΏΡΠ΄Π³ΠΎΡΠΎΠ²ΡΡ ΠΊΠΎΠ½ΡΠ΅Π½ΡΡ Π΄Π»Ρ: welcome / onboarding; engagement; winback; ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΠΉΠ½ΠΈΡ ΡΠΎΠ·ΡΠΈΠ»ΠΎΠΊ.
β’ Π‘ΠΏΡΠ²ΠΏΡΠ°ΡΡ Π· ΠΊΠΎΠΌΠ°Π½Π΄Π°ΠΌΠΈ CRM, ΠΌΠ°ΡΠΊΠ΅ΡΠΈΠ½Π³Ρ, Π΄ΠΈΠ·Π°ΠΉΠ½Ρ ΡΠ° ΠΊΠΎΠ½ΡΠ΅Π½ΡΡ.
β’ Π£ΡΠ°ΡΡΡ Π² A/B-ΡΠ΅ΡΡΠ°Ρ (Π·Π°ΠΌΡΠ½Π° ΡΠ΅ΠΌ, CTA, ΡΡΡΡΠΊΡΡΡΠΈ ΠΏΠΎΠ²ΡΠ΄ΠΎΠΌΠ»Π΅Π½Ρ).
β’ ΠΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³ Π±Π°Π·ΠΎΠ²ΠΈΡ ΠΌΠ΅ΡΡΠΈΠΊ (Open Rate, CTR, Delivery) ΡΠ° Π²Π½Π΅ΡΠ΅Π½Π½Ρ ΠΏΠΎΠΊΡΠ°ΡΠ΅Π½Ρ.
Π©ΠΎ Π΄Π»Ρ Π½Π°Ρ Π²Π°ΠΆΠ»ΠΈΠ²ΠΎ
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· email / push / SMS Π°Π±ΠΎ Π² ΡΠΎΠ»Ρ ΠΊΠΎΠ½ΡΠ΅Π½Ρ-ΠΌΠ΅Π½Π΅Π΄ΠΆΠ΅ΡΠ° Π²ΡΠ΄ 1 ΡΠΎΠΊΡ.
- Π£Π²Π°ΠΆΠ½ΡΡΡΡ Π΄ΠΎ Π΄Π΅ΡΠ°Π»Π΅ΠΉ Ρ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π°Π»ΡΠ½ΡΡΡΡ Π·Π° ΡΠ΅Π·ΡΠ»ΡΡΠ°Ρ.
- Π ΠΎΠ·ΡΠΌΡΠ½Π½Ρ, ΡΠΎ ΠΊΠΎΠ½ΡΠ΅Π½Ρ Ρ CRM β ΡΠ΅ ΡΠ°ΡΡΠΈΠ½Π° ΠΊΠΎΡΠΈΡΡΡΠ²Π°ΡΡΠΊΠΎΠ³ΠΎ ΡΡΠ΅Π½Π°ΡΡΡ, Π° Π½Π΅ ΠΎΠΊΡΠ΅ΠΌΡ ΠΏΠΎΠ²ΡΠ΄ΠΎΠΌΠ»Π΅Π½Π½Ρ.
- ΠΠ°Π·ΠΎΠ²Π° Π»ΠΎΠ³ΡΠΊΠ° ΡΠ΅Π³ΠΌΠ΅Π½ΡΠ°ΡΡΡ (ΠΊΠΎΠΌΡ, ΠΊΠΎΠ»ΠΈ Ρ Π½Π°Π²ΡΡΠΎ ΠΌΠΈ Π²ΡΠ΄ΠΏΡΠ°Π²Π»ΡΡΠΌΠΎ ΠΏΠΎΠ²ΡΠ΄ΠΎΠΌΠ»Π΅Π½Π½Ρ).
- ΠΠΎΡΠΎΠ²Π½ΡΡΡΡ ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ Π· ΡΡΡΠΈΠ½Π½ΠΈΠΌΠΈ Π·Π°Π΄Π°ΡΠ°ΠΌΠΈ ΡΠ° Π²Π΅Π»ΠΈΠΊΠΈΠΌ ΠΎΠ±ΡΡΠ³ΠΎΠΌ ΠΊΠ°ΠΌΠΏΠ°Π½ΡΠΉ.
- ΠΠ°ΠΆΠ°Π½Π½Ρ ΡΠΎΠ·Π²ΠΈΠ²Π°ΡΠΈΡΡ Π² Π½Π°ΠΏΡΡΠΌΠΊΡ CRM / retention.
ΠΠ»ΡΡΠΎΠΌ Π±ΡΠ΄Π΅:
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· CRM / ESP-ΠΏΠ»Π°ΡΡΠΎΡΠΌΠ°ΠΌΠΈ.
- ΠΠ°Π²ΠΈΡΠΊΠΈ ΠΊΠΎΠΏΡΡΠ°ΠΉΡΠΈΠ½Π³Ρ.
- ΠΠ°Π·ΠΎΠ²Π΅ ΡΠΎΠ·ΡΠΌΡΠ½Π½Ρ A/B-ΡΠ΅ΡΡΡΠ²Π°Π½Π½Ρ ΡΠ° Π°Π½Π°Π»ΡΡΠΈΠΊΠΈ.
ΠΠΎΠΆΠ»ΠΈΠ²ΠΎΡΡΡ ΡΠΎΡΡΡ
- Π ΠΎΠ·Π²ΠΈΡΠΎΠΊ Ρ Π½Π°ΠΏΡΡΠΌΠΊΡ CRM Manager / Retention Manager.
- Π ΡΠ°ΡΠΎΠΌ β Π·ΡΠΎΡΡΠ°Π½Π½Ρ Π΄ΠΎ CRM Lead Π°Π±ΠΎ Owner CRM-Π½Π°ΠΏΡΡΠΌΠΊΡ / ΠΏΡΠΎΡΠΊΡΡ.
- Π ΠΎΠ±ΠΎΡΠ° Π· ΡΠ΅Π°Π»ΡΠ½ΠΈΠΌΠΈ ΠΏΡΠΎΠ΄ΡΠΊΡΠ°ΠΌΠΈ ΡΠ° Π²Π΅Π»ΠΈΠΊΠΈΠΌΠΈ Π±Π°Π·Π°ΠΌΠΈ ΠΊΠΎΡΠΈΡΡΡΠ²Π°ΡΡΠ².
ΠΠΈ ΠΏΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ:
- ΠΡΠ΄ΡΡΡΠ½ΡΡΡΡ Π±ΡΡΠΎΠΊΡΠ°ΡΡΡ Π² ΠΏΡΠΎΡΠ΅ΡΠ°Ρ ΠΏΡΠΈΠΉΠ½ΡΡΡΡ ΡΡΡΠ΅Π½Ρ Ρ ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π±Π΅Π·ΠΏΠΎΡΠ΅ΡΠ΅Π΄Π½ΡΠΎ Π²ΠΏΠ»ΠΈΠ²Π°ΡΠΈ Π½Π° ΠΏΡΠΎΠ΄ΡΠΊΡ/ΠΏΡΠΎΡΠΊΡ.
- Skill Boost - ΠΊΠΎΠΌΠΏΠ΅Π½ΡΠ°ΡΡΡ Π·ΠΎΠ²Π½ΡΡΠ½ΡΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ ΡΠΏΡΠ²ΡΠΎΠ±ΡΡΠ½ΠΈΠΊΡΠ².
- ΠΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π½Π°Π²ΡΠ°ΡΠΈΡΡ β Π°Π±ΠΎ Π½Π°Π²ΡΠ°ΡΠΈ (ΠΌΠ°ΡΠΌΠΎ ΠΏΡΠΎΡΠΊΡΠΈ Π· ΡΠ½ΡΠ΅ΡΠ½Π°ΡΡΡΠΈ ΡΠ° ΠΌΠ΅Π½ΡΠΎΡΡΡΠ²Π°).
- Π Π΅Π°Π»ΡΠ·Π°ΡΡΡ ΡΠ΄Π΅ΠΉ ΡΠ΅ΡΠ΅Π· Π²Π»Π°ΡΠ½Ρ ΠΏΡΠΎΡΠΊΡΠΈ β ΠΠ΅ Π±ΡΠΉΡΠ΅ΡΡ Π΅ΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΡΠ²Π°ΡΠΈ! ΠΡΠΎΠΏΠΎΠ½ΡΠΉΡΠ΅ ΡΠ° ΠΎΠ²Π½Π΅ΡΡΡΡ ΠΏΡΠΎΡΠ΅Ρ ΡΠ΅Π°Π»ΡΠ·Π°ΡΡΡ.
- ΠΡΠ΄ΡΡΠΈΠΌΡΡΡΠ΅ ΡΠ΅ΡΠ΅Π΄ΠΎΠ²ΠΈΡΠ΅ ΡΠ° ΠΊΠΎΠΌΠ°Π½Π΄Π°, ΡΠ· ΡΠΊΠΎΡ ΠΌΠΎΠΆΠ½Π° ΡΠΎΠ±ΠΈΡΠΈ Π΄ΡΠΉΡΠ½ΠΎ ΠΊΡΡΡΡ ΠΏΡΠΎΠ΄ΡΠΊΡΠΈ, ΡΠΎ Π·ΠΌΡΠ½ΡΡΡΡ ΡΠΈΠ½ΠΎΠΊ.
- ΠΠ°ΡΠΏΠ»Π°ΡΡ ΡΡΠ²Π½Ρ IT-ΡΠΈΠ½ΠΊΡ ΡΠ° ΠΏΠΎΠ²Π½ΠΈΠΉ ΡΠΎΡΠΏΠ°ΠΊΠ΅Ρ (ΠΌΠ΅Π΄ΠΈΡΠ½Π° ΡΡΡΠ°Ρ ΠΎΠ²ΠΊΠ°, ΠΊΠΎΠ½ΡΡΠ»ΡΡΠ°ΡΡΡ ΡΠ΅ΡΠ°ΠΏΠ΅Π²ΡΠ° Π² ΠΎΡΡΡΡ, ΠΊΠΎΠΌΠΏΠ΅Π½ΡΠ°ΡΡΡ ΡΠΏΠΎΡΡΠ·Π°Π»Ρ, ΠΊΠΎΠΌΠΏΠ΅Π½ΡΠ°ΡΡΡ Π²Π°ΡΡΠΎΡΡΡ Π»Π°Π½ΡΡΠ² Π· Π΄ΠΎΡΡΠ°Π²ΠΊΠΎΡ ΡΠΎΡΠΎ).
- ΠΡΡΡΠ½ΠΈΠΉ ΠΎΡΡΡ Ρ ΡΠ΅Π½ΡΡΡ ΠΠΈΡΠ²Π° (ΠΏΡΡΠΊΠΈ Π·Ρ ΠΠ²ΡΡΠΈΠ½Π΅ΡΡΠΊΠΎΡ/ΠΠΈΠ±ΡΠ΄ΡΡΠΊΠΎΡ) ΡΠ· Π·Π΅Π»Π΅Π½ΠΎΡ ΠΏΠ°Π½ΠΎΡΠ°ΠΌΠ½ΠΎΡ ΡΠ΅ΡΠ°ΡΠΎΡ. ΠΡΠΎΠ±Π»Π΅ΠΌΠ° Π±Π»Π΅ΠΊΠ°ΡΡΡΠ² Π²ΠΈΡΡΡΠ΅Π½Π° Π½Π° 100%.
- ΠΡΠ΄ΠΏΡΡΡΠΊΠ° β Ρ ΡΠ΅Π±Π΅ Π±ΡΠ΄Π΅ 17 Π΄Π½ΡΠ² ΠΎΠΏΠ»Π°ΡΡΠ²Π°Π½ΠΎΡ Π²ΡΠ΄ΠΏΡΡΡΠΊΠΈ ΡΠ° 3 Π΅ΠΊΡΡΡΠ°Π²ΠΈΡ ΡΠ΄Π½Ρ β ΠΎΠ΄ΡΡΠΆΠ΅Π½Π½Ρ, Π½Π°ΡΠΎΠ΄ΠΆΠ΅Π½Π½Ρ Π΄ΠΈΡΠΈΠ½ΠΈ, Π½Π΅ΠΏΠ΅ΡΠ΅Π΄Π±Π°ΡΡΠ²Π°Π½Ρ ΠΏΠΎΠ΄ΡΡ ΡΠ° ΡΠ½ΡΠ΅.
- ΠΠΎΠ½ΡΡ Π·Π° ΡΠ΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°ΡΡΡ β ΠΠΈ Π·Π°Π²ΠΆΠ΄ΠΈ ΡΠ°Π΄ΡΡΠΌΠΎ ΡΠ° ΡΡΠ½ΡΡΠΌΠΎ ΡΠ΅, ΡΠΎ ΡΡΠΌΠΌΠ΅ΠΉΡΠΈ ΡΠ΅ΠΊΠΎΠΌΠ΅Π½Π΄ΡΡΡΡ ΡΠ²ΠΎΡΡ Π΄ΡΡΠ·ΡΠ², ΡΠΎΠΌΡ Π΄ΠΎ ΠΏΠ»ΡΡΡΠ² ΡΠΎΠ±ΠΎΡΠΈ Π· ΠΏΠ΅ΡΠ΅Π²ΡΡΠ΅Π½ΠΎΡ ΡΠ° Π½Π°Π΄ΡΠΉΠ½ΠΎΡ Π»ΡΠ΄ΠΈΠ½ΠΎΡ ΠΌΠΈ Π΄ΠΎΠ΄Π°ΡΠΌΠΎ Π±ΠΎΠ½ΡΡ.
- Π Π΅Π»ΠΎΠΊΠ΅ΠΉΡ β Π·ΠΌΡΠ½Π° ΠΌΡΡΡΠ° ΠΏΡΠΎΠΆΠΈΠ²Π°Π½Π½Ρ Π·Π°Π²ΠΆΠ΄ΠΈ ΡΠΏΠΎΠ½ΡΠΊΠ°Ρ Π΄ΠΎ Π΄ΠΎΠ΄Π°ΡΠΊΠΎΠ²ΠΈΡ Π²ΠΈΡΡΠ°Ρ, Π° Π½Π°Ρ Π±ΠΎΠ½ΡΡ Π΄ΠΎΠΏΠΎΠΌΠΎΠ³Π°Ρ ΠΏΡΠΎΠΉΡΠΈ ΡΠ΅ΠΉ ΠΏΠ΅ΡΡΠΎΠ΄ Π±Π΅Π· Π·Π°ΠΉΠ²ΠΈΡ ΡΡΡΠ΅ΡΡΠ².
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Β· 32 views Β· 2 applications Β· 6d
Data Project/Product Manager
Hybrid Remote Β· Ukraine Β· Product Β· 3 years of experience Β· English - B1"ΠΠ²ΡΠΎΡΠ°" β ΡΠ΅ ΡΡΡΠ°ΡΠ½ΠΈΠΉ Π±ΡΠ·Π½Π΅Ρ, ΡΠΎ ΠΏΠΎΡΠ°Π²ΡΡ 2011 ΡΠΎΠΊΡ Π½Π° ΠΠΎΠ»ΡΠ°Π²ΡΠΈΠ½Ρ. Π‘ΡΠΎΠ³ΠΎΠ΄Π½Ρ ΠΌΠ΅ΡΠ΅ΠΆΠ° Π½Π°Π»ΡΡΡΡ ΠΏΠΎΠ½Π°Π΄ 1800 ΠΌΠ°Π³Π°Π·ΠΈΠ½ΡΠ², 4 ΠΎΡΡΡΠΈ ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠΈ ΡΠ° 6 Π»ΠΎΠ³ΡΡΡΠΈΡΠ½ΠΈΡ Ρ Π°Π±ΡΠ² Π² Π£ΠΊΡΠ°ΡΠ½Ρ. ΠΠ°ΡΠ° ΠΊΠΎΠΌΠ°Π½Π΄Π° β ΡΠ΅ ΠΏΠΎΠ½Π°Π΄ 16000 Π°Π²ΡΠΎΡΡΠ²ΡΡΠ², ΡΠΊΡ ΠΊΠΎΠΆΠ΅Π½ Π΄Π΅Π½Ρ ΠΏΡΠ°ΡΡΡΡΡ Π½Π°Π΄ Π²ΡΡΠ»Π΅Π½Π½ΡΠΌ ΠΌΡΡΡΡ..."ΠΠ²ΡΠΎΡΠ°" β ΡΠ΅ ΡΡΡΠ°ΡΠ½ΠΈΠΉ Π±ΡΠ·Π½Π΅Ρ, ΡΠΎ ΠΏΠΎΡΠ°Π²ΡΡ 2011 ΡΠΎΠΊΡ Π½Π° ΠΠΎΠ»ΡΠ°Π²ΡΠΈΠ½Ρ. Π‘ΡΠΎΠ³ΠΎΠ΄Π½Ρ ΠΌΠ΅ΡΠ΅ΠΆΠ° Π½Π°Π»ΡΡΡΡ ΠΏΠΎΠ½Π°Π΄ 1800 ΠΌΠ°Π³Π°Π·ΠΈΠ½ΡΠ², 4 ΠΎΡΡΡΠΈ ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠΈ ΡΠ° 6 Π»ΠΎΠ³ΡΡΡΠΈΡΠ½ΠΈΡ Ρ Π°Π±ΡΠ² Π² Π£ΠΊΡΠ°ΡΠ½Ρ. ΠΠ°ΡΠ° ΠΊΠΎΠΌΠ°Π½Π΄Π° β ΡΠ΅ ΠΏΠΎΠ½Π°Π΄ 16000 Π°Π²ΡΠΎΡΡΠ²ΡΡΠ², ΡΠΊΡ ΠΊΠΎΠΆΠ΅Π½ Π΄Π΅Π½Ρ ΠΏΡΠ°ΡΡΡΡΡ Π½Π°Π΄ Π²ΡΡΠ»Π΅Π½Π½ΡΠΌ ΠΌΡΡΡΡ ΠΠ²ΡΠΎΡΠΈ: ΠΏΠΎΠΊΡΠ°ΡΡΠ²Π°ΡΠΈ ΠΏΠΎΠ²ΡΡΠΊΠ΄Π΅Π½Π½Π΅ ΠΆΠΈΡΡΡ Π»ΡΠ΄Π΅ΠΉ, ΡΠΎΠ±Π»ΡΡΠΈ ΡΠΎΠ²Π°ΡΠΈ Π΄Π»Ρ Π΄ΠΎΠΌΡ ΡΠ° Π΄ΡΡΡ Π΄ΠΎΡΡΡΠΏΠ½ΠΈΠΌΠΈ.
Π’Π²ΠΎΡ ΠΊΠ»ΡΡΠΎΠ²Ρ Π·Π°Π΄Π°ΡΡ:
- ΠΠΏΠΈΡ ΠΏΠΎΡΠΎΡΠ½ΠΈΡ
ΡΠΈΡΡΠ΅ΠΌ, Π΄ΠΆΠ΅ΡΠ΅Π» Ρ Π»ΠΎΠ³ΡΠΊΠΈ ΡΡΠ°Π½ΡΡΠΎΡΠΌΠ°ΡΡΠΉ Π΄Π°Π½ΠΈΡ
(Source specifications ; ETL/ELT process; ERD structure ; KPI calculations ); - Π£ΠΏΡΠ°Π²Π»ΡΠ½Π½Ρ ΠΏΡΠΎΡΠ΅ΡΠΎΠΌ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΈ ΡΠ° Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°ΡΡΡ Π°Π½Π°Π»ΡΡΠΈΡΠ½ΠΈΡ Π·Π²ΡΡΡΠ², ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ, Π΄ΠΆΠ΅ΡΠ΅Π» Π΄Π°Π½ΠΈΡ , ΠΌΠ΅ΡΡΠΈΠΊ Ρ KPI;
- Π£ΠΏΡΠ°Π²Π»ΡΠ½Π½Ρ JIRA Π΄Π»Ρ Π΄Π°ΡΠ°-ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ β ΠΎΠΏΠΈΡ, ΡΠΎΡΠΌΠ°Π»ΡΠ·Π°ΡΡΡ ΡΠ° ΠΊΠΎΠ½ΡΡΠΎΠ»Ρ ΡΠ΅ΡΠΌΡΠ½ΡΠ² Π²ΠΈΠΊΠΎΠ½Π°Π½Π½Ρ Π°Π½Π°Π»ΡΡΠΈΡΠ½ΠΈΡ ΡΠ° ΡΠ½ΠΆΠ΅Π½Π΅ΡΠ½ΠΈΡ Π·Π°Π²Π΄Π°Π½Ρ;
- Π£ΡΠ°ΡΡΡ Ρ ΠΏΡΡΠΎΡΠΈΡΠΈΠ·Π°ΡΡΡ Π±Π΅ΠΊΠ»ΠΎΠ³Ρ Π΄Π°ΡΠ°-ΠΏΡΠΎΡΠΊΡΡΠ² Ρ ΠΏΠ»Π°Π½ΡΠ²Π°Π½Π½Ρ ΡΠΏΡΠΈΠ½ΡΡΠ²;
- ΠΡΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠ° ΡΠ΅Ρ Π½ΡΡΠ½ΠΈΡ Π·Π°Π²Π΄Π°Π½Ρ (Π’Π) Π΄Π»Ρ Data Engineers, Π°Π½Π°Π»ΡΡΠΈΠΊΡΠ² Ρ Data Scientists;
- ΠΡΠΎΠ²Π΅Π΄Π΅Π½Π½Ρ Π·ΡΡΡΡΡΡΠ΅ΠΉ Π·Ρ ΡΡΠ΅ΠΉΠΊΡ ΠΎΠ»Π΄Π΅ΡΠ°ΠΌΠΈ Π΄Π»Ρ Π·Π±ΠΎΡΡ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΡ ΠΏΡΠΎ ΠΏΠΎΡΠΎΡΠ½Ρ Π±ΡΠ·Π½Π΅Ρ-ΠΏΡΠΎΡΠ΅ΡΠΈ ΡΠ° ΠΏΠΎΡΡΠ΅Π±ΠΈ Π² Π°Π½Π°Π»ΡΡΠΈΡΡ;
- ΠΠ°Π±Π΅Π·ΠΏΠ΅ΡΠ΅Π½Π½Ρ Π·Π²βΡΠ·ΠΊΡ ΠΌΡΠΆ Π±ΡΠ·Π½Π΅ΡΠΎΠΌ Ρ Π΄Π°ΡΠ°-ΠΊΠΎΠΌΠ°Π½Π΄ΠΎΡ, ΠΏΠ΅ΡΠ΅ΠΊΠ»Π°Π΄ βΠΌΠΎΠ²ΠΈ Π±ΡΠ·Π½Π΅ΡΡβ Ρ βΠΌΠΎΠ²Ρ Π΄Π°Π½ΠΈΡ β;
- ΠΠ½Π°Π»ΡΠ· ΡΡΠ½ΡΡΡΠΈΡ (legacy) ΡΡΡΠ΅Π½Ρ, Π²ΡΠ΄Π½ΠΎΠ²Π»Π΅Π½Π½Ρ Π»ΠΎΠ³ΡΠΊΠΈ ΡΠ° ΡΡΡΡΠΊΡΡΡΠΈ Π΄Π°Π½ΠΈΡ ;
- Π‘ΡΠ²ΠΎΡΠ΅Π½Π½Ρ ΡΠ° ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠ° ΠΊΠ°ΡΡΠΈ Π΄Π°Π½ΠΈΡ Ρ ΠΏΡΠΎΡΠ΅ΡΡΠ² (AS IS / TO BE).
ΠΠ°ΠΌ Π±ΡΠ΄Π΅ ΠΊΠ»Π°ΡΠ½ΠΎ ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ ΡΠ°Π·ΠΎΠΌ, ΡΠΊΡΠΎ ΡΠΈ:
- ΠΠ°ΡΡ Π²ΡΠ΄ 3+ ΡΠΎΠΊΡΠ² Π΄ΠΎΡΠ²ΡΠ΄Ρ Ρ Data Analysis / Project Management /Product Data Analysis ;
- ΠΠ°ΡΡ ΡΠΎΠ·ΡΠΌΡΠ½Π½Ρ Π°ΡΡ ΡΡΠ΅ΠΊΡΡΡΠΈ Π΄Π°Π½ΠΈΡ , ETL-ΠΏΡΠΎΡΠ΅ΡΡΠ², ΡΡΡΡΠΊΡΡΡΠΈ Π±Π°Π· Π΄Π°Π½ΠΈΡ (SQL - must);
- Π ΠΎΠ·ΡΠΌΡΡΡ ΡΠ»ΠΎΡ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΈ BI-Π·Π²ΡΡΡΠ² (Power BI, Metabase, Looker);
- ΠΠ°ΡΡ Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· Confluence / JIRA;
- ΠΠ°ΡΡ Π΄ΠΎΡΠ²ΡΠ΄ ΡΡΡΡΠΊΡΡΡΡΠ²Π°Π½Π½Ρ ΠΏΡΠΎΡΠ΅ΡΡΠ² Ρ ΡΡΠ²ΠΎΡΠ΅Π½Π½Ρ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°ΡΡΡ βΠ· Π½ΡΠ»Ρβ;
- ΠΠΌΡΡΡ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΡΠΈ ΡΠ½ΡΠ΅ΡΠ²βΡ Π·Ρ ΡΡΠ΅ΠΉΠΊΡ ΠΎΠ»Π΄Π΅ΡΠ°ΠΌΠΈ, ΡΠ°ΡΠΈΠ»ΡΡΡΠ²Π°ΡΠΈ Π·ΡΡΡΡΡΡΡ, Π·Π±ΠΈΡΠ°ΡΠΈ Π½Π΅ΡΠ²Π½Ρ Π²ΠΈΠΌΠΎΠ³ΠΈ.
ΠΡΠ΄Π΅ ΠΏΠ΅ΡΠ΅Π²Π°Π³ΠΎΡ, ΡΠΊΡΠΎ ΡΠΈ:
- Π ΠΎΠ·ΡΠΌΡΡΡ Π΄ΠΎΠΌΠ΅Π½ retail / e-commerce / digital / mobile
- Π‘Π°ΠΌΠΎΡΡΡΠΉΠ½ΠΎ ΠΌΠΎΠΆΠ΅Ρ ΠΏΡΠΎΠ²Π΅ΡΡΠΈ ΠΏΠ΅ΡΠ²ΠΈΠ½Π½Π΅ Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Π½Ρ Π΄Π°Π½ΠΈΡ ΡΠ° ΡΠΈΡΡΠ΅ΠΌΠ½ΠΎ ΡΠ΅Π°Π»ΡΠ·ΠΎΠ²ΡΠ²Π°Π² Data Quality Check;
- Π ΠΎΠ·ΡΠΌΡΡΡ ΠΏΡΠΈΠ½ΡΠΈΠΏΠΈ Data Governance;
- ΠΠ°Π² Π±Π΅Π·ΠΏΠΎΡΠ΅ΡΠ΅Π΄Π½ΡΠΉ Π΄ΠΎΡΠ²ΡΠ΄ Π· BigQuery / AWS / Power BI / MSSQL on-demand.
ΠΠ΅ΡΠ΅Π²Π°Π³ΠΈ ΡΠΎΠ±ΠΎΡΠΈ Π² ΠΠ²ΡΠΎΡΡ:
- ΠΠΎΠΌΡΠΎΡΡΠ½ΠΈΠΉ Π³ΡΠ°ΡΡΠΊ ΡΠΎΠ±ΠΎΡΠΈ
- ΠΠ½ΠΈΠΆΠΊΠ° 15% Π½Π° ΠΏΠΎΠΊΡΠΏΠΊΠΈ ΡΠΎΠ²Π°ΡΡΠ² Π² Π½Π°ΡΡΠΉ ΠΌΠ΅ΡΠ΅ΠΆΡ
- ΠΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ ΡΠ²ΠΈΠ΄ΠΊΠΎ Π·Π±ΡΠ΄ΡΠ²Π°ΡΠΈ Π³ΠΎΡΠΈΠ·ΠΎΠ½ΡΠ°Π»ΡΠ½Ρ ΡΠ° Π²Π΅ΡΡΠΈΠΊΠ°Π»ΡΠ½Ρ ΠΊΠ°Ρ'ΡΡΡ
- ΠΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ LEAN ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΡΡ (ΠΎΡΠ°Π΄Π»ΠΈΠ²Π΅ Π²ΠΈΡΠΎΠ±Π½ΠΈΡΡΠ²ΠΎ);
- ΠΠΎΠ½ΡΡΠΈ Π·Π° ΡΠ΄Π΅Ρ ΠΏΠΎΠΊΡΠ°ΡΠ΅Π½Ρ ΡΠΎΠ±ΠΎΡΠΈΡ ΠΏΡΠΎΡΠ΅ΡΡΠ²
- Π©ΠΎΡΠΈΠΆΠ½Π΅Π²Ρ ΠΎΠ½Π»Π°ΠΉΠ½ Π·Π±ΠΎΡΠΈ Π²ΡΡΡΡ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ ΡΠ· ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π·Π°Π΄Π°ΡΠΈ ΠΏΠΈΡΠ°Π½Π½Ρ Π³Π΅Π½Π΅ΡΠ°Π»ΡΠ½ΠΎΠΌΡ Π΄ΠΈΡΠ΅ΠΊΡΠΎΡΡ
- ΠΠ΅Π·ΠΊΠΎΡΡΠΎΠ²Π½Ρ ΠΊΡΡΡΠΈ Ρ ΡΡΠ΅Π½ΡΠ½Π³ΠΈ Π²ΡΠ΄ ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠ΅Π½ΡΡΡ
- ΠΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π½Π°Π²ΡΠ°ΡΠΈΡΡ Π½Π° Π±ΡΠ΄Ρ-ΡΠΊΠΈΡ Π·ΠΎΠ²Π½ΡΡΠ½ΡΡ ΠΏΠ»Π°ΡΡΠΎΡΠΌΠ°Ρ Π· ΡΠ°ΡΡΠΊΠΎΠ²ΠΎΡ Π°Π±ΠΎ ΠΏΠΎΠ²Π½ΠΎΡ ΠΊΠΎΠΌΠΏΠ΅Π½ΡΠ°ΡΡΡΡ Π²Π°ΡΡΠΎΡΡΡ
- Π£Π½ΡΠΊΠ°Π»ΡΠ½Π° ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½Π° ΠΊΡΠ»ΡΡΡΡΠ°, ΡΡΠΊΠ°Π²Ρ ΡΠ²Π΅Π½ΡΠΈ ΡΠ° Π·Π°Ρ ΠΎΠ΄ΠΈ
- ΠΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ ΡΠ½ΡΡΡΡΠ²Π°ΡΠΈ ΡΠ° Π΄ΠΎΠ»ΡΡΠ°ΡΠΈΡΡ Π΄ΠΎ Π±Π»Π°Π³ΠΎΠ΄ΡΠΉΠ½ΠΈΡ ΠΏΡΠΎΡΠΊΡΡΠ²
- Baby box Π΄Π»Ρ Π½ΠΎΠ²ΠΎΠ½Π°ΡΠΎΠ΄ΠΆΠ΅Π½ΠΈΡ Π°Π²ΡΠΎΡΡΠΈΠΊΡΠ²
- ΠΠ΅Π·ΠΊΠΎΡΡΠΎΠ²Π½Π° ΡΡΠΈΠ΄ΠΈΡΠ½Π° ΠΊΠΎΠ½ΡΡΠ»ΡΡΠ°ΡΡΡ
- ΠΠ΅ΠΉΠΌΠΎΠ²ΡΡΠ½Π΅ ΡΠΏΠΎΡΡΠΈΠ²Π½Π΅ ΠΊΠΎΠΌβΡΠ½ΡΡΡ Π· ΡΠ΅Π³ΡΠ»ΡΡΠ½ΠΈΠΌΠΈ ΡΠ΅Π»Π΅Π½Π΄ΠΆΠ°ΠΌΠΈ ΡΠ° ΠΏΡΠΈΠ·Π°ΠΌΠΈ
ΠΠΎΠ΄Π°ΡΠΊΠΎΠ²Ρ ΠΏΠ΅ΡΠ΅Π²Π°Π³ΠΈ:
- ΠΠΈΡΠΊΠΎΠ½Ρ-ΠΊΠ»ΡΠ± Π²ΡΠ΄ ΠΏΠ°ΡΡΠ½Π΅ΡΡΠ²;
- Π¦ΡΠΊΠ°Π²Π΅ ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½Π΅ ΠΆΠΈΡΡΡ ΡΠ° ΡΠΎΡΡΠ°Π»ΡΠ½Ρ Π·Π°Ρ ΠΎΠ΄ΠΈ, ΡΠ΅Π»Π΅Π½Π΄ΠΆΡ, Π±ΡΠ³ΠΎΠ²ΠΈΠΉ ΡΠ° ΡΡΡΠ±ΠΎΠ»ΡΠ½ΠΈΠΉ ΠΊΠ»ΡΠ±ΠΈ;
- ΠΡΠ±Π»ΡΠΎΡΠ΅ΠΊΠ°, ΡΠΈΡΠ°ΡΡΠΊΠΈΠΉ ΠΊΠ»ΡΠ± ΡΠ° Π±Π°Π³Π°ΡΠΎ ΡΠ½ΡΠΈΡ ΡΠ΅ΡΠ²ΡΡΡΠ² ΡΡΡΠ±ΠΎΡΠΈ!
ΠΠΎΡΠΈΡΠ½Π΅ Π΄Π»Ρ ΡΠ΅Π±Π΅:
- ΠΠ»Ρ ΠΏΡΠ°ΡΠ΅Π²Π»Π°ΡΡΡΠ²Π°Π½Π½Ρ Π½Π° ΠΏΠ΅ΡΡΠΎΠ΄ Π²ΠΎΡΠ½Π½ΠΎΠ³ΠΎ ΡΡΠ°Π½Ρ ΠΎΠ±ΠΎΠ²βΡΠ·ΠΊΠΎΠ²ΠΎ Π΄Π»Ρ ΡΠΎΠ»ΠΎΠ²ΡΠΊΡΠ² ΡΡΠ΅Π±Π° ΠΌΠ°ΡΠΈ ΠΏΡΠΈ ΡΠΎΠ±Ρ Π΄ΡΠΉΡΠ½ΠΈΠΉ Π΄ΠΎΠΊΡΠΌΠ΅Π½Ρ ΠΏΡΠΎ Π²ΡΠΉΡΡΠΊΠΎΠ²ΠΈΠΉ ΠΎΠ±Π»ΡΠΊ.
- ΠΠ»Ρ Π½Π°Ρ Π½Π΅ Π²Π°ΠΆΠ»ΠΈΠ²ΠΎ ΡΠ΅ ΡΠ²ΠΎΡ ΠΏΠ΅ΡΡΠ° ΡΠΎΠ±ΠΎΡΠ° ΡΠΈ ΡΠΈ ΠΌΠ°ΡΡ Π±Π°Π³Π°ΡΠΎΡΡΡΠ½ΠΈΠΉ Π΄ΠΎΡΠ²ΡΠ΄ β ΠΌΠΈ ΡΡΠ½ΡΡΠΌΠΎ Π² ΡΠ°Π»Π°Π½ΡΠ°Ρ Π±Π°ΠΆΠ°Π½Π½Ρ Π²ΡΠΈΡΠΈΡΡ ΡΠ° ΡΠΎΠ·Π²ΠΈΠ²Π°ΡΠΈΡΡ!
- ΠΠΏΠΈΡ ΠΏΠΎΡΠΎΡΠ½ΠΈΡ
ΡΠΈΡΡΠ΅ΠΌ, Π΄ΠΆΠ΅ΡΠ΅Π» Ρ Π»ΠΎΠ³ΡΠΊΠΈ ΡΡΠ°Π½ΡΡΠΎΡΠΌΠ°ΡΡΠΉ Π΄Π°Π½ΠΈΡ
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Β· 118 views Β· 2 applications Β· 30d
AI Optimization Specialist, ΠΠ Integrator
Office Work Β· Ukraine (Kyiv) Β· 1 year of experience Β· English - None MilTech πͺΠ¨ΡΠΊΠ°ΡΠΌΠΎ AI Optimization Specialist, ΠΠ Integrator. Π©ΠΎ ΡΡΠ΅Π±Π° Π±ΡΠ΄Π΅ ΡΠΎΠ±ΠΈΡΠΈ: ΠΠ½Π°Π»ΡΠ·ΡΠ²Π°ΡΠΈ Π±ΡΠ·Π½Π΅Ρ-ΠΏΡΠΎΡΠ΅ΡΠΈ β Π²ΡΠ΄ ΡΠ΅ΠΊΡΡΡΠΈΠ½Π³Ρ Π΄ΠΎ Π²ΠΈΡΠΎΠ±Π½ΠΈΡΡΠ²Π° β Ρ Π·Π½Π°Ρ ΠΎΠ΄ΠΈΡΠΈ ΠΌΡΡΡΡ, Π΄Π΅ AI ΠΌΠΎΠΆΠ΅ Π·Π΅ΠΊΠΎΠ½ΠΎΠΌΠΈΡΠΈ ΡΠ°Ρ, Π³ΡΠΎΡΡ ΡΠΈ Π½Π΅ΡΠ²ΠΈ. ΠΠ½ΡΠ΅Π³ΡΡΠ²Π°ΡΠΈ AI-ΡΡΡΠ΅Π½Π½Ρ: ΡΠ°Ρ-Π±ΠΎΡΠΈ, ΡΠΊΡΠΈΠΏΡΠΈ, ΡΠΈΡΡΠ΅ΠΌΠΈ...Π¨ΡΠΊΠ°ΡΠΌΠΎ AI Optimization Specialist, ΠΠ Integrator.
Π©ΠΎ ΡΡΠ΅Π±Π° Π±ΡΠ΄Π΅ ΡΠΎΠ±ΠΈΡΠΈ:
- ΠΠ½Π°Π»ΡΠ·ΡΠ²Π°ΡΠΈ Π±ΡΠ·Π½Π΅Ρ-ΠΏΡΠΎΡΠ΅ΡΠΈ β Π²ΡΠ΄ ΡΠ΅ΠΊΡΡΡΠΈΠ½Π³Ρ Π΄ΠΎ Π²ΠΈΡΠΎΠ±Π½ΠΈΡΡΠ²Π° β Ρ Π·Π½Π°Ρ ΠΎΠ΄ΠΈΡΠΈ ΠΌΡΡΡΡ, Π΄Π΅ AI ΠΌΠΎΠΆΠ΅ Π·Π΅ΠΊΠΎΠ½ΠΎΠΌΠΈΡΠΈ ΡΠ°Ρ, Π³ΡΠΎΡΡ ΡΠΈ Π½Π΅ΡΠ²ΠΈ.
- ΠΠ½ΡΠ΅Π³ΡΡΠ²Π°ΡΠΈ AI-ΡΡΡΠ΅Π½Π½Ρ: ΡΠ°Ρ-Π±ΠΎΡΠΈ, ΡΠΊΡΠΈΠΏΡΠΈ, ΡΠΈΡΡΠ΅ΠΌΠΈ Π²ΡΠ΄Π΅ΠΎΠ°Π½Π°Π»ΡΡΠΈΠΊΠΈ, ΠΏΠΎΡΡΠΊ ΠΏΠΎ Π±Π°Π·Π°Ρ , Π°Π²ΡΠΎΠΌΠ°ΡΠΈΡΠ½Ρ ΠΎΠ±ΡΠΎΠ±ΠΊΡ Π΄Π°Π½ΠΈΡ .
- ΠΡΠ΄Π±ΠΈΡΠ°ΡΠΈ ΡΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠΈ: Π²ΡΠ΄ ChatGPT API Ρ Claude Π΄ΠΎ Zapier, Make, Python-ΡΠΊΡΠΈΠΏΡΡΠ² ΡΠΈ Power BI β ΡΡΠ΅, ΡΠΎ Π΄ΠΎΠΏΠΎΠΌΠ°Π³Π°Ρ.
Π’Π΅ΡΡΡΠ²Π°ΡΠΈ, Π΅ΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΡΠ²Π°ΡΠΈ, ΠΏΠΎΠΊΠ°Π·ΡΠ²Π°ΡΠΈ ΡΠ΅Π·ΡΠ»ΡΡΠ°Ρ.
Π’ΠΈ ΡΠ΄Π΅Π°Π»ΡΠ½ΠΎ Π½Π°ΠΌ ΠΏΡΠ΄Ρ ΠΎΠ΄ΠΈΡ, ΡΠΊΡΠΎ:
- ΠΠ½Π°ΡΡ, ΡΠΊ ΠΏΡΠ°ΡΡΡΡΡ ΡΡΡΠ°ΡΠ½Ρ AI-ΠΌΠΎΠ΄Π΅Π»Ρ (ChatGPT, Claude, Midjourney, Perplexity, Llama Ρ Ρ.Π΄.).
- ΠΠΎΠΆΠ΅Ρ ΠΎΠ±'ΡΠ΄Π½Π°ΡΠΈ ΠΊΡΠ»ΡΠΊΠ° ΡΠ½ΡΡΡΡΠΌΠ΅Π½ΡΡΠ² Π² ΠΎΠ΄ΠΈΠ½ ΡΠΎΠ±ΠΎΡΠΈΠΉ ΠΏΡΠΎΡΠ΅Ρ (ΡΠ΅ΡΠ΅Π· API, ΡΠ½ΡΠ΅Π³ΡΠ°ΡΠΎΡΠΈ Π°Π±ΠΎ ΠΏΡΠΎΡΡΠΎ Π»ΠΎΠ³ΡΠΊΡ).
- ΠΠΌΡΡΡ ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ Π· Π΄Π°Π½ΠΈΠΌΠΈ (ΡΠ°Π±Π»ΠΈΡΡ, Π±Π°Π·ΠΈ, CSV, SQL, Python, Power Automate β Π±ΡΠ΄Ρ-ΡΠΎ).
- ΠΠ΅ ΠΏΡΠΎΡΡΠΎ Β«ΠΊΠΎΡΠΈΡΡΡΡΡΡΡ AIΒ», Π° ΡΠΎΠ·ΡΠΌΡΡΡ, ΡΠΊ ΠΉΠΎΠ³ΠΎ Π·ΠΌΡΡΠΈΡΠΈ ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ Π½Π° ΡΠ΅Π·ΡΠ»ΡΡΠ°Ρ.
Π Π³ΠΎΠ»ΠΎΠ²Π½Π΅ β Ρ ΡΠ΅Π±Π΅ Ρ Π·Π΄ΠΎΡΠΎΠ²ΠΈΠΉ ΡΠΊΠ΅ΠΏΡΠΈΡ Π΄ΠΎ ΡΡΠ°Π· ΡΠΈΠΏΡ Β«ΡΠ°ΠΊ Π·Π°Π²ΠΆΠ΄ΠΈ ΡΠΎΠ±ΠΈΠ»ΠΈΒ».
ΠΡΠ΄Π΅ ΠΏΠ»ΡΡΠΎΠΌ:
- ΠΠΎΡΠ²ΡΠ΄ Ρ Π°Π²ΡΠΎΠΌΠ°ΡΠΈΠ·Π°ΡΡΡ Π±ΡΠ·Π½Π΅Ρ-ΠΏΡΠΎΡΠ΅ΡΡΠ², Π°Π½Π°Π»ΡΡΠΈΡΡ Π°Π±ΠΎ DevOps.
ΠΠΌΡΠ½Π½Ρ ΡΠΎΠ±ΠΈΡΠΈ MVP ΡΠ²ΠΈΠ΄ΠΊΠΎ (Ρ ΠΏΠΎΡΡΠΌ ΡΠΆΠ΅ Π΄ΠΎΠ²ΠΎΠ΄ΠΈΡΠΈ Π΄ΠΎ ΡΠΎΠ·ΡΠΌΡ).
Π©ΠΎ ΠΌΠΈ ΠΏΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ:
- ΠΠΎΠ½ΠΊΡΡΠ΅Π½ΡΠ½Π° Π·Π°ΡΠΎΠ±ΡΡΠ½Π° ΠΏΠ»Π°ΡΠ°
- ΠΡΡΡΡΠΉΠ½Π΅ ΠΏΡΠ°ΡΠ΅Π²Π»Π°ΡΡΡΠ²Π°Π½Π½Ρ, ΡΡΠ°Π±ΡΠ»ΡΠ½Ρ Π²ΠΈΠΏΠ»Π°ΡΠΈ Π±Π΅Π· Π·Π°ΡΡΠΈΠΌΠΎΠΊ.
- Π‘Π²ΠΎΠ±ΠΎΠ΄Ρ Π΅ΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΡΠ²: ΡΠΊΡΠΎ Ρ ΡΠ΄Π΅Ρ β ΡΠ΅ΡΡΡΠΉ.
- ΠΡΡΡ Π±ΡΠ»Ρ ΠΌ. ΠΠ°ΡΠΈΠ»ΡΠΊΡΠ²ΡΡΠΊΠ° (Ρ Π³Π΅Π½Π΅ΡΠ°ΡΠΎΡ, ΡΠΊΡΠΈΡΡΡ, ΡΡΠ°Π±ΡΠ»ΡΠ½ΠΈΠΉ ΡΠ½ΡΠ΅ΡΠ½Π΅Ρ).
- ΠΡΠ°ΡΡΠΊ: ΠΠ½-ΠΡ, Π· 9:00 Π΄ΠΎ 18:00
ΠΠ°Π²Π°, Π±Π΅Π·ΠΊΠΎΡΡΠΎΠ²Π½Ρ ΠΎΠ±ΡΠ΄ΠΈ, Π·ΠΎΠ½ΠΈ Π²ΡΠ΄ΠΏΠΎΡΠΈΠ½ΠΊΡ.
Π₯ΠΎΡΠ΅Ρ Π½Π΅ ΠΏΡΠΎΡΡΠΎ Β«ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ Π· AIΒ», Π° Π²ΠΈΠΊΠΎΡΠΈΡΡΠΎΠ²ΡΠ²Π°ΡΠΈ ΠΉΠΎΠ³ΠΎ, ΡΠΎΠ± Π·ΠΌΡΠ½ΡΠ²Π°ΡΠΈ ΡΠΏΠΎΡΡΠ± ΡΠΎΠ±ΠΎΡΠΈ? Π’ΠΎΠ΄Ρ ΡΠΈ β Π½Π°Ρ ΠΊΠ°Π½Π΄ΠΈΠ΄Π°Ρ.
ΠΠ°Π΄ΡΠΈΠ»Π°ΠΉ ΡΠ΅Π·ΡΠΌΠ΅ β Π°Π±ΠΎ ΠΊΡΠ°ΡΠ΅, ΠΏΠΎΠΊΠ°ΠΆΠΈ, ΡΠΎ Π²ΠΆΠ΅ ΠΎΠΏΡΠΈΠΌΡΠ·ΡΠ²Π°Π². π
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Β· 72 views Β· 14 applications Β· 14d
Junior AI Engineer
Ukraine Β· Product Β· 1 year of experience Β· English - NoneΠΡΠΎ ΠΏΡΠΎΡΠΊΡ: Zakupivli.pro β Π½Π°ΠΉΠ±ΡΠ»ΡΡΠΈΠΉ ΠΌΠ°ΠΉΠ΄Π°Π½ΡΠΈΠΊ Π΄Π΅ΡΠΆΠ°Π²Π½ΠΈΡ ΡΠ° ΠΊΠΎΠΌΠ΅ΡΡΡΠΉΠ½ΠΈΡ ΡΠΎΡΠ³ΡΠ², ΠΎΡΡΡΡΠΉΠ½ΠΈΠΉ ΡΡΠ°ΡΠ½ΠΈΠΊ ΡΠΈΡΡΠ΅ΠΌΠΈ Π΅Π»Π΅ΠΊΡΡΠΎΠ½Π½ΠΈΡ Π΄Π΅ΡΠΆΠ°Π²Π½ΠΈΡ Π·Π°ΠΊΡΠΏΡΠ²Π΅Π»Ρ Prozorro. Π§Π΅ΡΠ΅Π· Π½Π°Ρ ΠΠ°ΡΡΠΎΠ½Π°Π»ΡΠ½Π° ΠΏΠΎΠ»ΡΡΡΡ ΠΊΡΠΏΡΡ ΠΊΠΎΡΠΌ Π΄Π»Ρ ΡΡΠΎΡΠΎΠΆΠΎΠ²ΠΈΡ ΡΠΎΠ±Π°ΠΊ, Π° ΠΠΠΠ ΠΏΡΠΎΠ΄Π°Ρ Π΄Π΅ΡΠΆΠ°Π²Ρ Π±Π΅Π½Π·ΠΈΠ½. Π£ Π½Π°Ρ Ρ...ΠΡΠΎ ΠΏΡΠΎΡΠΊΡ:
Zakupivli.pro β Π½Π°ΠΉΠ±ΡΠ»ΡΡΠΈΠΉ ΠΌΠ°ΠΉΠ΄Π°Π½ΡΠΈΠΊ Π΄Π΅ΡΠΆΠ°Π²Π½ΠΈΡ ΡΠ° ΠΊΠΎΠΌΠ΅ΡΡΡΠΉΠ½ΠΈΡ ΡΠΎΡΠ³ΡΠ², ΠΎΡΡΡΡΠΉΠ½ΠΈΠΉ ΡΡΠ°ΡΠ½ΠΈΠΊ ΡΠΈΡΡΠ΅ΠΌΠΈ Π΅Π»Π΅ΠΊΡΡΠΎΠ½Π½ΠΈΡ Π΄Π΅ΡΠΆΠ°Π²Π½ΠΈΡ Π·Π°ΠΊΡΠΏΡΠ²Π΅Π»Ρ Prozorro.Π§Π΅ΡΠ΅Π· Π½Π°Ρ ΠΠ°ΡΡΠΎΠ½Π°Π»ΡΠ½Π° ΠΏΠΎΠ»ΡΡΡΡ ΠΊΡΠΏΡΡ ΠΊΠΎΡΠΌ Π΄Π»Ρ ΡΡΠΎΡΠΎΠΆΠΎΠ²ΠΈΡ ΡΠΎΠ±Π°ΠΊ, Π° ΠΠΠΠ ΠΏΡΠΎΠ΄Π°Ρ Π΄Π΅ΡΠΆΠ°Π²Ρ Π±Π΅Π½Π·ΠΈΠ½. Π£ Π½Π°Ρ Ρ Π²Π΅Π±-ΡΠ΅ΡΠ²ΡΡ, ΠΌΠΎΠ±ΡΠ»ΡΠ½ΠΈΠΉ Π΄ΠΎΠ΄Π°ΡΠΎΠΊ ΡΠ° Π½Π°Π²ΡΠ°Π»ΡΠ½Π° ΠΏΠ»Π°ΡΡΠΎΡΠΌΠ° Π΄Π»Ρ Π·Π°ΠΌΠΎΠ²Π½ΠΈΠΊΡΠ² ΡΠ° ΠΏΠΎΡΡΠ°ΡΠ°Π»ΡΠ½ΠΈΠΊΡΠ².
ΠΠΈ ΡΠΎΠ·ΡΠΎΠ±Π»ΡΡΠΌΠΎ AI-ΡΡΡΠ΅Π½Π½Ρ Π΄Π»Ρ ΠΏΠ»Π°ΡΡΠΎΡΠΌΠΈ Π·Π°ΠΊΡΠΏΡΠ²Π΅Π»Ρ Ρ ΠΏΡΠ°ΡΡΡΠΌΠΎ Π· ΡΡΠ·Π½ΠΈΠΌΠΈ Π½Π°ΠΏΡΡΠΌΠΊΠ°ΠΌΠΈ ΡΡΡΡΠ½ΠΎΠ³ΠΎ ΡΠ½ΡΠ΅Π»Π΅ΠΊΡΡ β Π²ΡΠ΄ ΡΠ°Ρ-Π±ΠΎΡΡΠ² Π΄ΠΎ Π°Π½Π°Π»ΡΠ·Ρ ΡΠ΅ΠΊΡΡΡΠ² Ρ Π²Π΅Π»ΠΈΠΊΠΈΡ ΠΌΠΎΠ²Π½ΠΈΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ. Π’ΡΡ ΡΠΈ ΠΎΡΡΠΈΠΌΠ°ΡΡ Π΄ΠΎΡΠ²ΡΠ΄ Ρ Π±Π°Π³Π°ΡΡΠΎΡ ΡΡΡΠ°ΡΠ½ΠΈΡ ΡΠ΅Ρ Π½ΠΎΠ»ΠΎΠ³ΡΡΡ Ρ ΡΡΠ²ΠΎΡΡΠ²Π°ΡΠΈΠΌΠ΅Ρ ΠΏΡΠΎΠ΄ΡΠΊΡ, ΡΠΊΠΈΠΉ ΡΠ΅Π°Π»ΡΠ½ΠΎ Π΄ΠΎΠΏΠΎΠΌΠ°Π³Π°Ρ ΡΠΊΡΠ°ΡΠ½ΡΡΠΌ. ΠΠΈ Π΄Π°ΠΌΠΎ ΡΡΠΊΠ°Π²Ρ Π·Π°Π΄Π°ΡΡ Ρ ΠΏΡΠ΄ΡΡΠΈΠΌΠ°ΡΠΌΠΎ ΡΠ²ΡΠΉ ΡΠΎΠ·Π²ΠΈΡΠΎΠΊ.
Π’Π΅Ρ Π½ΡΡΠ½Ρ Π²ΠΈΠΌΠΎΠ³ΠΈ- ΠΠΌΡΠ½Π½Ρ ΠΏΡΠΎΠ³ΡΠ°ΠΌΡΠ²Π°ΡΠΈ Π½Π° Python
- Π ΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΡΠΎΠ³ΠΎ, ΡΠΊ ΠΏΡΠ°ΡΡΡΡΡ Π²Π΅Π±-Π΄ΠΎΠ΄Π°ΡΠΊΠΈ ΡΠ° ΠΊΠΎΠΌΠΏ'ΡΡΠ΅ΡΠ½Ρ ΠΌΠ΅ΡΠ΅ΠΆΡ
- Π ΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΠΏΡΠΈΠ½ΡΠΈΠΏΡΠ² Π·Π±Π΅ΡΠ΅ΠΆΠ΅Π½Π½Ρ Π΄Π°Π½ΠΈΡ ΡΠ° ΡΠΎΠ±ΠΎΡΠΈ Π· Π½ΠΈΠΌΠΈ
- ΠΠ°Π·ΠΎΠ²Π΅ ΡΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΠΊΠ»Π°ΡΠΈΡΠ½ΠΎΠ³ΠΎ ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ
- Π ΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΠΏΡΠΈΠΊΠ»Π°Π΄Π½ΠΎΡ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΠΊΠΈ, ΡΠΊΠ° Π²ΠΈΠΊΠΎΡΠΈΡΡΠΎΠ²ΡΡΡΡΡΡ Π΄Π»Ρ ΠΏΠΎΠ±ΡΠ΄ΠΎΠ²ΠΈ ML Π°Π»Π³ΠΎΡΠΈΡΠΌΡΠ²
- Π ΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΠΏΡΠΈΠ½ΡΠΈΠΏΡΠ² Ρ Π΄ΠΎΡΠ²ΡΠ΄ Π½Π°ΠΏΠΈΡΠ°Π½Π½Ρ ΠΏΡΠΎΠΌΠΏΡΡΠ² Π΄Π»Ρ Π²Π΅Π»ΠΈΠΊΠΈΡ ΠΌΠΎΠ²Π½ΠΈΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ
ΠΠ°ΠΆΠ»ΠΈΠ²ΠΎ- ΠΠΈΠ²ΠΈΠΉ ΡΠ½ΡΠ΅ΡΠ΅Ρ Π΄ΠΎ ΡΠ΅Ρ Π½ΠΎΠ»ΠΎΠ³ΡΠΉ ΡΠ° ΡΠΎΠ±ΠΎΡΠΈ ΡΡΡΡΠ½ΠΎΠ³ΠΎ ΡΠ½ΡΠ΅Π»Π΅ΠΊΡΡ, Π±Π°ΠΆΠ°Π½Π½Ρ Ρ Π²ΠΌΡΠ½Π½Ρ ΡΠ°ΠΌΠΎΡΡΡΠΉΠ½ΠΎ Π½Π°Π²ΡΠ°ΡΠΈΡΡ
- ΠΠ°ΡΠ²Π½ΡΡΡΡ ΠΏΠ΅Ρ-ΠΏΡΠΎΡΠΊΡΡΠ² Π°Π±ΠΎ ΡΠ°ΠΌΠΎΡΡΡΠΉΠ½ΠΈΡ ΡΠΏΡΠΎΠ± ΡΡΠ²ΠΎΡΠ΅Π½Π½Ρ ΠΏΡΠΎΠ³ΡΠ°ΠΌ
- ΠΠΌΡΠ½Π½Ρ ΠΏΠΎΡΠ΄Π½ΡΠ²Π°ΡΠΈ ΡΠ΅ΠΎΡΠ΅ΡΠΈΡΠ½Ρ Π·Π½Π°Π½Π½Ρ Π· ΡΡ Π·Π°ΡΡΠΎΡΡΠ²Π°Π½Π½ΡΠΌ Ρ ΡΡΠ²ΠΎΡΠ΅Π½Π½Ρ ΠΏΡΠΎΠ³ΡΠ°ΠΌ
- ΠΠΈ Π΄ΡΠΆΠ΅ ΡΡΠ½ΡΡΠΌΠΎ Π΄ΠΎΠΏΠΈΡΠ»ΠΈΠ²ΡΡΡΡ Ρ ΡΠΎΠ·ΡΠΌΡΠ½Π½Ρ Π½Π΅ ΡΡΠ»ΡΠΊΠΈ "ΡΠΊ ΠΏΡΠ°ΡΡΡ", Π° ΠΉ "ΠΊΠΎΠ»ΠΈ Ρ Π½Π°Π²ΡΡΠΎ Π²ΠΈΠΊΠΎΡΠΈΡΡΠΎΠ²ΡΠ²Π°ΡΠΈ"
ΠΡΠ΄Π΅ ΠΏΠ»ΡΡΠΎΠΌ- ΠΠ»ΠΈΠ±ΡΠ΅ ΡΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ½ΠΈΡ
ΠΎΡΠ½ΠΎΠ² ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ ΡΠ° Π²ΠΌΡΠ½Π½Ρ ΡΡ
ΠΏΡΠΎΠ³ΡΠ°ΠΌΡΠ²Π°ΡΠΈ:
- Π²Π΅ΠΊΡΠΎΡΠΈ ΡΠ° ΠΌΠ΅ΡΠΎΠ΄ΠΈ ΡΡ ΠΏΠΎΡΡΠ²Π½ΡΠ½Π½Ρ
- ΡΡΠ·Π½ΠΈΡΡ ΠΌΡΠΆ Π½Π°ΠΏΡΡΠΌΠΊΠΎΠΌ Π²Π΅ΠΊΡΠΎΡΠ° Ρ Π΄ΠΎΠ²ΠΆΠΈΠ½ΠΎΡ Π²Π΅ΠΊΡΠΎΡΠ°
- Π°Π»Π³ΠΎΡΠΈΡΠΌΠΈ k Π½Π°ΠΉΠ±Π»ΠΈΠΆΡΠΈΡ ΡΡΡΡΠ΄ΡΠ² (KNN) ΡΠ° Π»ΡΠ½ΡΠΉΠ½Π° ΡΠ΅Π³ΡΠ΅ΡΡΡ
- ΠΌΠ°ΡΡΠΈΡΠ½Π΅ ΠΌΠ½ΠΎΠΆΠ΅Π½Π½Ρ
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· Π²ΠΈΠ±ΡΡΠΊΠ°ΠΌΠΈ Π΄Π°Π½ΠΈΡ
- ΠΠΎΡΠ²ΡΠ΄ Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ AI ΠΏΠΎΠΌΡΡΠ½ΠΈΠΊΡΠ² (Clode Code, Cursor, Copilot Ρ Ρ. ΠΏ.)
- ΠΠ½Π°Π½Π½Ρ ΠΌΠ΅ΡΡΠΈΠΊ ΠΏΠΎΠ΄ΡΠ±Π½ΠΎΡΡΡ (cosine similarity vs euclidean distance) ΡΠ° ΡΠΎΠ·ΡΠΌΡΠ½Π½Ρ, Π΄Π»Ρ ΡΠΊΠΈΡ
Π²ΠΈΠΏΠ°Π΄ΠΊΡΠ² Π²ΠΎΠ½ΠΈ ΠΏΡΠ΄Ρ
ΠΎΠ΄ΡΡΡ
ΠΠΈ ΠΏΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ: - ΠΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π±Π΅Π·ΠΏΠΎΡΠ΅ΡΠ΅Π΄Π½ΡΠΎ Π²ΠΏΠ»ΠΈΠ²Π°ΡΠΈ Π½Π° ΡΠΎΠ·Π²ΠΈΡΠΎΠΊ Π½Π°ΡΠΎΠ³ΠΎ ΠΏΡΠΎΠ΄ΡΠΊΡΡ ΡΠ° Π²ΠΏΡΠΎΠ²Π°Π΄ΠΆΡΠ²Π°ΡΠΈ ΡΠ½Π½ΠΎΠ²Π°ΡΡΠΉΠ½Ρ ΡΡΡΠ΅Π½Π½Ρ.
- ΠΡΠΎΡΠ΅ΡΡΠΉΠ½ΠΈΠΉ ΡΠΎΠ·Π²ΠΈΡΠΎΠΊ: Π‘ΠΏΡΠΈΡΡΠΌΠΎ ΠΎΡΠΎΠ±ΠΈΡΡΡΡΠ½ΠΎΠΌΡ ΡΠ° ΠΏΡΠΎΡΠ΅ΡΡΠΉΠ½ΠΎΠΌΡ Π·ΡΠΎΡΡΠ°Π½Π½Ρ ΠΊΠΎΠΆΠ½ΠΎΠ³ΠΎ ΡΠ»Π΅Π½Π° ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ. ΠΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ ΡΠ°ΠΌΠΎΠΌΡ ΠΎΠ±ΡΠ°ΡΠΈ ΡΠ° Π²ΠΈΠΊΠΎΡΠΈΡΡΠΎΠ²ΡΠ²Π°ΡΠΈ ΡΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠΈ.
- ΠΠ½Π½ΠΎΠ²Π°ΡΡΠΉΠ½Ρ ΠΏΡΠΎΠ΅ΠΊΡΠΈ: Π ΠΎΠ±ΠΎΡΠ° Π· Π½ΠΎΠ²ΡΡΠ½ΡΠΌΠΈ AI ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΡΡΠΌΠΈ Ρ ΠΌΠ°ΡΡΡΠ°Π±Π½ΠΎΠΌΡ ΠΏΡΠΎΠ΅ΠΊΡΡ Π΄Π΅ΡΠΆΠ°Π²Π½ΠΎΠ³ΠΎ Π·Π½Π°ΡΠ΅Π½Π½Ρ.
24 Π΄Π½Ρ ΠΎΠΏΠ»Π°ΡΡΠ²Π°Π½ΠΎΡ Π²ΡΠ΄ΠΏΡΡΡΠΊΠΈ ΡΠ° Π½Π΅ΠΎΠ±ΠΌΠ΅ΠΆΠ΅Π½Π° ΠΊΡΠ»ΡΠΊΡΡΡΡ Π»ΡΠΊΠ°ΡΠ½ΡΠ½ΠΈΡ . - ΠΠ΅Π΄ΠΈΡΠ½Π΅ ΡΡΡΠ°Ρ ΡΠ²Π°Π½Π½Ρ ΠΏΡΡΠ»Ρ Π°Π΄Π°ΠΏΡΠ°ΡΡΠΉΠ½ΠΎΠ³ΠΎ ΠΏΠ΅ΡΡΠΎΠ΄Ρ.
- ΠΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½ΠΈΠΉ ΠΏΡΠΈΡ
ΠΎΠ»ΠΎΠ³ Ρ ΠΏΡΠΈΡ
ΠΎΠ»ΠΎΠ³ΡΡΠ½Π° ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠ° Π²ΡΠ΄ Π·ΠΎΠ²Π½ΡΡΠ½ΡΡ
ΡΠ°Ρ
ΡΠ²ΡΡΠ².
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