Jobs Kyiv, ML / AI

Data Science UA is a service company with deep expertise in AI and Data Science. Our story started in 2016 with the first Data Science UA Conference in Kyiv, and since then, we’ve built one of the largest AI communities in Europe.

About the role:
We are looking for a hands-on Sr. Machine Learning / Computer Vision Engineer with strong practical experience in designing, training, evaluating, and improving vision systems for real-world applications. The ideal candidate combines solid theoretical ML/CV fundamentals with an engineering mindset and is comfortable taking ownership of the full pipeline, from data preparation and experimentation to model optimization and deployment.

Responsibilities:
- Design, train, evaluate, and improve machine learning and computer vision models for real-world production use cases
- Build and maintain end-to-end ML pipelines, including data collection support, preprocessing, feature engineering, training, validation, and inference
- Develop solutions across both computer vision and machine learning tasks depending on business needs
- Perform error analysis, diagnose model weaknesses, and drive improvements in accuracy, robustness, and reliability
- Select and justify appropriate methods and model architectures based on dataset characteristics, product constraints, and deployment requirements
- Work with challenging real-world data, including noisy, limited, imbalanced, or weakly labeled datasets
- Collaborate with engineering and product teams to translate business problems into practical ML solutions
- Contribute to production-ready development with a focus on maintainability, reproducibility, and performance

Requirements:
- 3–5+ years of professional experience in Machine Learning / Computer Vision
- Strong senior-level practical expertise in computer vision, machine learning, and applied model development
- Hands-on experience with tasks such as object detection, image classification, anomaly detection, feature-based approaches, or similar
- Solid understanding of classical ML methods, including tree-based models, linear models, feature engineering, model selection, and evaluation
- Strong Python skills and practical experience with PyTorch, OpenCV, and common ML tooling
- Experience building full ML workflows including data preparation, augmentation, preprocessing, training, validation, testing, and deployment handoff
- Strong understanding of model evaluation, debugging, overfitting, generalization, optimization, and experiment-driven improvement
- Ability to write clean, modular, maintainable code and independently own technical solutions
- Strong analytical thinking, engineering maturity, and problem-solving skills

Nice to Have:
- Experience in adjacent ML domains such as time-series, audio, or NLP
- Experience with embedding-based methods, metric learning, retrieval systems, or memory-bank approaches
- Practical experience with model optimization techniques such as quantization, pruning, distillation, or related efficiency-focused approaches
- Experience working with real-world industrial datasets and ambiguous problem formulations
- Knowledge of software engineering best practices, reproducible experimentation, and pipeline design

We offer:
- Free English classes with a native speaker and external courses compensation;
- PE support by professional accountants;
- Medical insurance;
- Team-building events, conferences, meetups, and other activities;
- There are many other benefits you’ll find out at the interview.

Data Science UA is a service company with deep expertise in AI and Data Science. Our story started in 2016 with the first Data Science UA Conference in Kyiv, and since then, we’ve built one of the largest AI communities in Europe.

About the client:
Our client is an IT company that develops technological solutions and products to help companies reach their full potential and meet the needs of their users. The team comprises over 600 specialists in IT and Digital, with solid expertise in various technology stacks necessary for creating complex solutions.

About the role:
We are seeking an experienced Data Scientist with a passion for large language models (LLMs) and cutting-edge AI research. In this role, you will design and prototype data preparation pipelines, collaborating closely with data engineers to transform your prototypes into scalable production pipelines, design and implement a state-of-the-art evaluation and benchmarking framework to measure and guide model quality, and do end-to-end LLMs training. You will work alongside top AI researchers and engineers, ensuring our models are not only powerful but also aligned with user needs, cultural context, and ethical standards.

Responsibilities:
- Curation of datasets for pre-training, supervised fine-tuning, and alignment
- Research and develop best practices and novel techniques in LLM training and evaluation pipelines.
- Collaborate closely with data engineers, annotators, linguists, and domain experts to scale data processes, define evaluation tasks and collect high-quality feedback.

Requirements:
Education & Experience:
- 3+ years of experience in Data Science or Machine Learning, preferably with a focus on NLP.
- An advanced degree (Master’s or PhD) in Computer Science, Computational Linguistics, Machine Learning, or a related field is highly preferred.
GenAI & NLP Expertise:
- Practical experience with fine-tuning LLMs / VLMs models
- Hands-on experience with modern NLP approaches, including embedding models, semantic search, text classification, sequence tagging (NER), transformers/LLMs, RAGs.
ML & Programming Skills:
- Strong experience with deep learning frameworks such as PyTorch or JAX for building models.
- Ability to write efficient, clean code and debug complex model issues.

Nice-to-have:
Advanced NLP/ML Techniques:
- Applied experience using Reinforcement Learning in NLP / LLM settings
- Prior work on LLM safety, fairness, and bias mitigation.
- Experience generating and curating synthetic datasets for Supervised Fine-Tuning (SFT), including quality control and scaling considerations.
Research & Community:
- Publications in NLP/ML conferences or contributions to open-source NLP projects.
- Active participation in the AI community or demonstrated continuous learning (e.g., Kaggle competitions, research collaborations) indicates a passion for staying at the forefront of the field.
MLOps & Infrastructure:
- Hands-on experience with containerization (Docker) and orchestration (Kubernetes) for ML, as well as ML workflow tools (MLflow, Airflow).
- Experience in working alongside MLOps engineers to streamline the deployment and monitoring of NLP models.
- Experience with cloud platforms (AWS, GCP, or Azure) and big data technologies (Spark, Hadoop, Ray, Dask) for scaling data processing or model training is a plus.
Problem-Solving:
- Innovative mindset with the ability to approach open-ended AI problems creatively.
- Comfort in a fast-paced R&D environment where you can adapt to new challenges, propose solutions, and drive them to implementation

The company offers:
- Office or remote — it’s up to you. You can work from anywhere, and we will arrange your workplace
- Remote onboarding
- We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners
- Health and life insurance
- Wellbeing program and corporate psychologist
- Reimbursement of expenses for Kyivstar mobile communication

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 evolved—unlocking entirely new capabilities for our teams and our clients’ 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 

We present an engaging opportunity to explore and work with various technologies beyond ChatGPT prompts. You’ll have the flexibility to transition between teams, enabling you to contribute to diverse projects, including complex LLM training pipelines, 3D generative AI, diffusion models, and multimodal edge ML.

Our team comprises experts in the foundational elements of next-generation AI systems, encompassing multimodal inference, generative reasoning, and robust training pipelines. We also maintain an in-house GPU cluster, providing resources for interacting, training, and experimenting with larger models for both professional projects and personal exploration.

Joining our team — means joining a knowledgeable group of researchers and engineers in an environment eager to stay at the forefront of AI innovation, a critical endeavor in today’s rapidly advancing AI landscape.

Requirements:
• Strong Python Experience (1 year +)
• Experience with building Generative AI projects
• Specialized experience with LLMs, LangChain, LangGraph, LangFuse, RAG, and related technologies
• Experience in building REST APIs, knowledge of Docker, relational & vector DBs
• At least upper intermediate written/spoken English
• Be able to visit the office at least 3 times a week

Would be a plus:
• Experience with building Voice-to-Voice AI Systems using LiveKit or similar frameworks
• Knowledge of existing yet fresh AI tools, AI marketplaces, etc.
• Knowledge of various machine learning methodologies, including classic machine learning, recommendation engines, natural language processing, computer vision, and beyond
• C/C++ knowledge
• Experience in edge ML

Key Responsibilities:
• Tackle tough problems and find creative ways to solve them
• Maintain and optimize the solution for maximum speed and flexibility
• Guide, tune, and train LLMs
• Write clean and reusable code
• Improve your skills and stay up-to-date with emerging technologies

What We Offer:
• Startup culture, a strong goal-oriented team, and a research mindset
• Opportunity to leverage your engineering skills for fellow engineers and shape the future of AI
• Working with the newest technical equipment (Latest MacBook Pro)
• 20 working days of annual vacation leave
• English courses, Educational Events & Conferences
• Medical insurance

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 → training → 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.

Interested in joining our team? We invite you to submit your CV.

<By submitting your CV to LLC “GigaCloud”, EDRPOU code [39792589] (hereinafter referred to as the “Company”), 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 “On Personal Data Protection”, ISO 27701 Information Privacy Management System, and the provisions of the GDPR>.

We are a British—Ukrainian air defence tech company building distributed systems across the frontline. We are looking for a Founding Engineer with deep expertise in Machine Learning and Computer Vision to take full ownership of the architecture and implementation of detection systems for our current and future product lines.

Our core value is impact for Ukraine: we build technology that makes a real difference on the actual battlefield, not in labs or on paper specs. We operate with a deep-tech mindset, pushing new technologies where engineering rigor truly matters. We value ownership and responsibility—people who execute, deliver, and stand behind the results.

We especially value engineers with strong analytical thinking and proven problem-solving skills — such as participation in mathematical/programming olympiads or experience contributing to open-source projects.

Key Responsibilities

• Detection Systems Development: Build and maintain the full lifecycle of ML solutions across the company’s product lines.
• Inference Engineering: Optimize models for real-time operations.
• Backlog Execution & Implementation:
  • Develop RF Classification models (Radio Frequency signals).
  • Improve the accuracy of DoA (Direction of Arrival) algorithms.
  • Implement drone behavior analysis and pilot localization algorithms.
• Best Practices: Define the architecture, tooling, and approaches to build a scalable ML infrastructure from the ground up.

Skills & Requirements

• Strong theoretical background in Linear Algebra, Probability, and Statistics.
• Experience with Computer Vision models: Classification, Object Recognition, and Tracking.
• Python + relevant ML libraries, PyTorch.
• Experience taking models to production (Production ML).
• Hands-on experience with inference engines.
• Ability to build low-latency, real-time detection pipelines.
• Proficiency in C++ and/or CUDA for building high-performance modules.

Nice to Have

• Experience in DefenseTech, SigInt (Signals Intelligence), or Embedded Systems.
• Understanding of Radio Frequency (RF) physics.

We Offer

• Meaningful and high-impact work in the AIR defense domain
• Practical R&D environment with real autonomy
• Direct influence on technical decisions and the product direction
• Work in an experienced senior engineering team
• Сlear, fast, senior-to-senior communication with a minimum number of team meetings
• Office in the center of Kyiv (available for onsite work when required)
• Full-time position
• Standard business hours; some tasks may require involvement outside the usual schedule (testing, critical updates)

We are seeking a highly technical Machine Learning Engineer to work onsite with a client team in Kyiv, supporting multiple customers and delivering production-grade ML solutions.

This role has a strong emphasis on ML Ops, model deployment, and computer vision, with additional exposure to Palantir Foundry (pipelines and UI). The successful candidate will be comfortable working independently in environments with uncertain or evolving requirements, while collaborating closely with both onsite and remote teams.

Key Responsibilities:
 

• Design, develop, train, fine-tune, and deploy machine learning models into production environments.
• Build and maintain ML Ops pipelines, including model versioning, deployment, monitoring, and retraining.
• Develop and support computer vision solutions for real-world business use cases.
• Work with structured and unstructured data to deliver scalable ML solutions from PoC → MVP → Production.
• Use Docker to containerize ML workloads and ensure portability and reproducibility.
• Contribute to and maintain Palantir Foundry pipelines and UI components (prior experience strongly preferred; training can be provided).
• Collaborate with cross-functional teams (engineering, product, client stakeholders) both onsite and remotely.
• Clearly communicate technical approaches, trade-offs, and results to non-technical stakeholders.
• Proactively drive progress and decision-making, even when requirements are ambiguous.
• Analyze data to find patterns and create machine learning solutions for challenging business issues
• Understand the AI/ML program journey to formulate relevant high impact business questions that can be answered through data analysis.
   

Required Skills & Experience:
 

• 3+ years of hands-on experience in Machine Learning, including model training, fine-tuning, and deployment, production ML systems
• Strong experience with Docker for ML workloads.
• Proficient with ML Ops concepts (CI/CD for ML, model lifecycle management, monitoring).
• Hands-on experience with PyTorch, TensorFlow, Keras, advanced Python skills (NumPy, Pandas, Scikit-learn, etc.).
• Experience working with cloud platforms (AWS, Azure, or similar).
• Familiarity with SQL for data analysis.
• Ability to work independently and take ownership of delivery.
• Fluency in English (spoken and written).
• Strong interpersonal skills with the ability to translate client requests into technical solutions and explain complex ML topics succinctly to technical and non-technical audiences

Strongly Preferred / Nice to Have:
 

• Prior experience with Palantir Foundry:Data pipelines, Foundry applications / UI
• Experience with computer vision use cases.
• Experience working in agile delivery environments.

ML/CV engineer

We’re looking for a passionate Machine Learning / Computer Vision Engineer to join our team.

As a member of our team, you will participate in research & development of solutions in the field of computer vision, document understanding using cutting-edge machine learning approaches. The position will involve different aspects of R&D including initial research, analysis, prototyping and development. By joining our team you’ll be able to affect Ukrainian Deftech area innovations and contribute to important today’s military products.

Responsibilities:

• Research and development of Image Processing algorithms including CV algorithms
• Research and prototyping of detection and tracking algorithms using ML and CV
• Work with data collection and analysis in order to improve efficiency of ML/CV dependent algorithms

Job Qualification:

• 2 years of commercial experience with Python
• Demonstrated hands-on experience with TensorFlow, PyTorch
• Practical Experience with Machine Learning, including designing, training, fine-tuning of ML models, and integrating machine learning systems into production environments related to Computer Vision, Document Understanding
• Experience with Object Tracking area using ML/CV
• Experience with vision transformer, vision encoder-decoder architectures
• Strong analytical and communication skills

Will be a plus:

• Experience in Miltech development
• Experience with code performance optimization
• Master’s or Bachelor’s degree in computer science, math, statistics, or related field
• Experience in C/C++ 

Working Conditions:

• official employment 
• offline work for growing deftech company (remote is also option but mostly offline)
• military exemption

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 isn’t 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 “super-investors.”

Through our generative AI technology implemented into brokerage platforms and other financial institutions’ 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:

• 3+ 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.

Client

Our client is a leading legal recruiting company aiming to build a data-driven platform specifically designed for lawyers and law firms. The platform brings everything together in one place — news and analytics, real-time deal and case tracking from multiple sources, firm and lawyer profiles enriched with cross-linked insights, rankings, and more.

Project overview

The platform aggregates data from hundreds of public sources, including law firm websites, deal announcements, legal databases, and media publications, creating a unified ecosystem of structured and interconnected legal data.

It combines AI-driven enrichment, automated data processing, and scalable infrastructure to ensure comprehensive and reliable coverage of the legal market.

Position overview

We are looking for a Lead AI/ML Engineer who will also take ownership of AI architecture, technical strategy, and team mentorship.

Responsibilities

• Develop and deploy AI/ML models leveraging GenAI (OpenAI API) for natural language understanding, summarization, and insights extraction
• Build named entity recognition (NER) and entity linking solutions tailored to legal domain data (law firms, cases, deals, people)
• Implement scalable NLP pipelines for processing news, legal documents, and transaction data from multiple sources
• Design, train, and evaluate ML models to improve search, classification, and recommendation features
• Collaborate with AWS teams to deploy and maintain models using SageMaker, manage datasets on S3, and ensure reliable operation and scalability
• Integrate AI capabilities seamlessly into the web platform, working alongside front-end and backend engineers
• Continuously research new AI models and NLP techniques relevant to legal data and user experience

Requirements

• Strong experience designing and implementing end-to-end AI/ML solutions in production environments.
• Hands-on experience with GenAI, including practical usage of the OpenAI API.
• Solid background in NLP, with hands-on experience in Named Entity Recognition (NER) and entity linking.
• Hands-on experience working with AWS, including services such as SageMaker and S3.
• Strong Python skills with practical experience using TensorFlow, PyTorch, and Hugging Face Transformers.
• Practical experience designing and implementing RAG (Retrieval-Augmented Generation) solutions.
• Proven experience building and implementing Recommendation Engines.

Nice to have

• Experience architecting scalable AI/ML systems on Amazon Web Services.
• Experience working with complex, data-intensive machine learning pipelines.
• Experience combining NLP, GenAI, and recommendation systems within a single solution.

We are seeking a Senior ML to join our AI & Data project. In this role, you will combine high-end machine learning engineering with a revolutionary approach to software delivery. You will not just build AI; you will build AI using AI, orchestrating agentic workflows to deliver complex solutions at a velocity traditional teams cannot match.

You will focus on building practical, production-ready solutions that bridge the gap between unstructured data and structured logic using LLMs, agentic workflows, and knowledge representations (ontologies, knowledge graphs). You are expected to be an "AI-Native" pioneer, utilizing tools like Claude Code, Cursor, Antigravity, and custom MCP servers to automate your own development lifecycle - from data exploration and model evaluation to code generation and documentation.

Requirements:

• 4+ years of professional experience in machine learning, data science, or AI engineering.
• Software development background 
• Strong proficiency in Python and the modern ML/AI ecosystem (e.g., PyTorch, Hugging Face, LangChain/LangGraph, Scikit-learn).
• Hands-on experience with data ingestion, RAG pipeline optimization, model evaluation, deployment (MLOps), and monitoring.
• Deep understanding of generative AI (LLMs, embeddings, RAG, prompt engineering, and agentic reasoning) and its practical constraints (latency, cost, safety, hallucinations).
• Experience turning complex business needs into "machine-ready" technical specifications and acceptance criteria.
• Strong experience with major cloud platforms; hands-on Azure knowledge (Azure AI Search, Azure OpenAI) is highly desirable.
• Evidence of using modern GenAI tools (Claude Code, GitHub Copilot, etc.) to significantly accelerate your development and testing process.
• Good English to work in a multinational team

Responsibilities: 

• Work with stakeholders to translate domain-specific knowledge into "Spec-Driven" ML architectures and agentic workflows.
• Design and implement solutions that combine the reasoning power of LLMs with the precision of structured knowledge (ontologies/knowledge graphs).
• Pilot the Claude Code CLI and other agentic tools to generate code, run automated tests, and maintain "Context Hygiene" within the project repository.
• Apply structured 4-phase debugging to ML pipelines, focusing on root-cause analysis of hallucinations, retrieval failures, and data drift.
• Define and automate "Skills" (prompt libraries, evaluation scripts, and deployment templates) to be re-used across multiple AI-Native pods.
• Define and implement quality gates, safety metrics, and cost-control practices for GenAI components.
• Lead by example in adopting AI-Native practices, mentoring the AI Apprentice and other team members in the "People + Agents" delivery model.
• Strong problem-solving and follow-up skills; must be proactive and take initiative
• Work independently on development tasks with a minimal amount of supervision

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, you’ll experience an inclusive culture of acceptance and belonging, where you’ll 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. You’ll 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, you’ll 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 what’s possible and bring new solutions to market. In the process, you’ll 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, you’re 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.

N-iX is looking for a Senior Machine Learning Engineer in Kyiv. You will be responsible for designing, developing, and deploying machine learning models at scale within the Palantir Foundry ecosystem. You will collaborate closely with data scientists, MLOps engineers, and data engineers to build robust, production-grade ML workflows—from data preparation and feature engineering to model training, evaluation, deployment, and monitoring.

Company provides military reservation (after successfully passing trial period).
 

Key Responsibilities

• Design and implement scalable ML models for use in predictive analytics, forecasting, and classification tasks.
• Work with Palantir Foundry to build end-to-end ML pipelines, including custom Python code, Foundry Functions, and Ontology-aware feature generation.
• Collaborate with Data Engineers to ensure high-quality, model-ready data flows from ingestion to inference.
• Operationalize models using industry best practices for versioning, reproducibility, and monitoring (e.g., via MLflow or native Foundry tools).
• Contribute to MLOps automation, including CI/CD for ML, drift detection, retraining pipelines, and evaluation dashboards.
• Partner with business stakeholders and domain experts to translate scientific or commercial hypotheses into model-based solutions.
• Apply rigorous experimentation and statistical validation to ensure models are explainable, generalizable, and regulatory-compliant.
• Stay informed on the latest developments in ML/AI and proactively introduce innovative techniques and frameworks.

Must-Have Skills & Experience

• 3+ years of experience in machine learning or applied data science, ideally in a production or enterprise setting.
• Strong programming skills in Python, with deep experience in machine learning libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Experience designing and deploying ML workflows at scale, preferably with experience in Foundry, KubeFlow, SageMaker, or similar platforms.
• Familiarity with feature engineering, data imputation, sampling strategies, and evaluation techniques 
• Hands-on experience with model deployment and monitoring, including logging metrics, detecting drift, and managing model lifecycles.
• Comfort working with structured and unstructured data: tabular, time series, text, etc.
• Solid understanding of data security, privacy, and compliance.
• Strong communication and stakeholder engagement skills; capable of explaining complex models in simple terms.
• English level at least Upper-Intermediate. 
   

Will be a plus: 

• Experience with Palantir Foundry.
   

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

Middle Computer Vision & ML Engineer — Founding Team

About Us

We are a newly funded MilTech startup building an on-premises platform for automated annotation of petabytes of UAV video and training computer vision models for autonomous flight. We have a strategic partnership with the largest Ukrainian UAV manufacturer and access to what is the largest privately owned UAV video dataset in the world. We are at the very beginning — the technical plan exists, the funding is secured, the data is real — and now we need the right people to turn it into reality.

The Role

We are looking for a Middle CV/ML Engineer to join as one of the first engineers on the team. You will work closely with the technical lead to build the ML pipeline from the ground up — implementing core components across data processing, model training, and deployment.

This is an early-stage startup, so the tech stack and processes are still being shaped. You will have real input into the tools and approaches we adopt, and your work will directly define how the platform operates. We are looking for someone who is hands-on, curious, and comfortable building things that don't exist yet.

What You Will Work On

Data Pipeline & Preprocessing
- Build video preprocessing pipelines: clip segmentation, frame extraction, scene detection, quality filtering
- Implement embedding extraction and data curation workflows for selecting diverse training subsets from a massive video corpus
- Prepare and export datasets in standard formats for training and annotation

Model Training & Experimentation
- Train and evaluate computer vision models for object detection, classification, tracking, and segmentation
- Run experiments, track results, and iterate on model architectures and hyperparameters
- Implement data augmentation strategies for robustness across weather, lighting, and occlusion conditions
- Contribute to distributed multi-GPU training pipelines

Active Learning & Annotation Support
- Implement auto-labeling pipelines with confidence-based routing
- Build tooling around the annotation platform (pre-annotation, format conversion, quality validation)
- Maintain automated quality checks for label consistency

Edge Deployment
- Export and optimize models for inference on NVIDIA Jetson (ONNX, TensorRT, FP16/INT8 quantization)
- Run accuracy and latency benchmarks on edge devices
- Help maintain the model delivery pipeline from training to deployment

What We Are Looking For

Must Have
- 3+ years of hands-on experience in computer vision and deep learning
- Solid PyTorch skills — comfortable writing training loops, custom datasets, and model code
- Experience with at least one detection or segmentation framework (YOLO family, Detectron2, MMDetection, or similar)
- Understanding of model evaluation metrics (mAP, IoU, precision/recall)
- Familiarity with experiment tracking (MLflow, W&B, or similar)
- Python as primary language; clean, well-structured code
- Comfortable working in Linux and containerized environments (Docker)

Nice to Have
- Model optimization experience (ONNX export, TensorRT, quantization)
- NVIDIA Jetson or other edge/mobile deployment
- Multi-object tracking (ByteTrack, DeepSORT, or similar)
- Experience with video processing pipelines (FFmpeg, OpenCV, decord)
- Data curation or annotation tools (FiftyOne, CVAT, Label Studio)
- Distributed training (DDP, Ray Train)
- UAV / drone / robotics or MilTech domain experience

Proposed Tech Stack

This is our starting point — the stack is still being finalized, and you will have input into the choices we make.

- Training: PyTorch, distributed training (DDP/FSDP) 
- Data processing: Ray Data or equivalent scalable framework 
- Data curation: FiftyOne, embedding-based selection 
- Annotation: CVAT with pre-annotation and active learning 
- Experiment tracking: MLflow 
- Edge: ONNX → TensorRT → NVIDIA Jetson 
- Infrastructure: Kubernetes, on-prem GPU cluster 
- Storage: S3-compatible object storage (Ceph) 

What We Offer

- Join an early-stage team where your contributions shape the product from day one
- Work across the full ML pipeline — not just one narrow piece
- The largest privately owned UAV video dataset in the world — petabyte-scale, impossible to replicate
- Dedicated on-prem GPU resources — no cloud queues or budget negotiations for compute
- Open-source-first approach with no vendor lock-in
- Grow fast in a small team with direct mentorship from the technical lead
- Competitive salary
- Stock option
 

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 → training → evaluation → deployment → 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).

• Надаємо бронювання від мобілізації

ПрАТ «БАНК ФАМІЛЬНИЙ» шукає інженера, який допоможе автоматизувати внутрішні процеси бек-офісу за допомогою AI-агентів, скриптів та інтеграцій.
 

Робота у нас це:

• команда висококваліфікованих експертів, що сприяє навчанню та професійному зростанню;
• сучасне корпоративне технічне обладнання та необхідні інструменти, які необхідні для ефективної роботи та реалізації проектів;
• зручний графік роботи;
• робота з офісу поруч із станцією метро Деміївська;
• офісний спортивний зал, який дає змогу підтримувати фізичну форму без зайвих витрат часу;
• смаколики та свіжі фрукти це лише частина нашої культури піклування та уваги до кожного члена команди.
   

Вашими завданнями буде:

• аналіз процесів технічної підтримки та бек-офісу;
• створення AI-агентів для внутрішніх процесів;
• інтеграція AI-інструментів з внутрішніми системами;
• робота з SQL та даними процесингу;
• інтеграція API зовнішніх сервісів;
• написання скриптів для автоматизації;
• аналіз транзакційних даних та операційних процесів;
• автоматизація внутрішніх процесів із використанням AI-інструментів.
   

Можливості:

• розвиток у сфері програмування: набуття досвіду в області розробки на Python через рішення нестандартних задач, розробку власних скриптів та програмного забезпечення, що дозволить вирішувати специфічні завдання та підвищувати ефективність робочих процесів;
• створення власних інструментів автоматизації та AI-рішень;
• залучення до технічної оптимізації, удосконаленням інтегрованих систем та розв'язанням задач у сфері обробки даних та управління процесами.
   

У нашого кандидата є:

• вища технічна освіта, освітній ступінь Бакалавр. Студенти, які перебувають на останньому курсі бакалаврату, також розглядатимуться;
• знання СУБД, а саме досвід у формулюванні SQL-запитів, включаючи:
• базове використання операторів SELECT, INSERT, UPDATE, DELETE для маніпулювання даними.
• розширений аналіз даних та здатність виконувати складні запити, що включають об'єднання даних з двох і більше таблиць за допомогою операторів JOIN, а також групування та фільтрацію даних з використанням GROUP BY та HAVING.
• досвід роботи з API.
• досвід роботи з AI / LLM-інструментами.

Якщо ви маєте базові знання у сфері інформаційних технологій та комп’ютерних наук, прагнете розширити свій професійний досвід та хочете застосувати свої технічні навички в реальних проектах, ми запрошуємо вас приєднатися до нашої команди. 
 

Надсилайте Ваше CV! Ми впевнені, що Ви шукали саме цю вакансію)