Jobs Kyiv

MacPaw is a software company that develops and distributes software for macOS and iOS. Today, we have 20 million active users across all our products.

At MacPaw, we believe humans and technology can reach their greatest potential together.

MacPaw is proud to be Ukrainian. The support and development of Ukraine are significant parts of the company’s culture. MacPaw gathers open-minded people who support each other and aspire to change the world around us.

We are building a world-class AI research unit and are looking for an experienced AI Research Scientist to strengthen our team. Since this unit is still young, this role offers a unique opportunity to shape its direction, contribute to its growth, and help establish it as a leader in AI research.

At our company, you’ll be working with the latest trends in the industry, conducting cutting-edge research, and bridging the gap between academic advancements and real-world applications. You'll have the chance to develop AI solutions that power products used by millions of users, ensuring that your innovations have a tangible impact.

If you are passionate about pushing the boundaries of AI research, publishing at top-tier conferences, and applying research to large-scale products, we’d love to hear from you!

In this role, you will:

• Drive cutting-edge research in fields critical to our AI research unit’s objectives, leading to innovative solutions and contributions to scientific advancement in key directions (e.g. Local LLMs, Agents, Reinforcement Learning, 3D, etc.)
• Take ownership of research initiatives from ideation to implementation, and personally conduct key aspects of the research
• Bridge the gap between advanced research and real-world applications by integrating state-of-the-art research results into our products 
• Collaborate with cross-functional teams to ensure that scientific innovations enhance product functionality and deliver measurable value to the customers
• Deliver high-impact research that results in publications accepted at top-tier AI conferences (e.g., NeurIPS, ACL, CVPR). Represent the organization as a speaker, establishing the research team as a world-class unit through exceptional contributions and scientific discourse
• Organize and conduct knowledge-sharing sessions for research teams and stakeholders, covering analysis methods, research processes, and successful implementation cases
• Provide mentoring and opportunities for students and other fellow employees
   

Skills you’ll need to bring:

• Prior experience as an AI Research Scientist with a proven innovation track record
• Strong record of publications, preferably at top-tier AI conferences like NeurIPS, ICML, CVPR, ECCV, ICLR, etc.
• Proven expertise in Large Language Models (LLMs) and Multimodal LLMs (MLLMs), hands-on experience with training, fine-tuning, and optimizing models for various applications
• Experience in leading research initiatives from ideation to deployment
• Proven ability to bridge academic research with industry needs by developing scalable AI solutions that create measurable value
• Experience in translating cutting-edge research into practical applications, integrating state-of-the-art models into real-world products and production environments
• Experience mentoring junior researchers, students, and colleagues in AI domains
• Advanced level of English
   

As a plus:

• Experience working in academic, corporate, or government AI research labs, contributing to cutting-edge advancements

What we offer:

• We are a Ukrainian company, and we stand with Ukraine against the russian aggression
  We maintain workplaces for the mobilized Macpawians and provide financial support to colleagues or their families affected by the war. Here, you can also read about the MacPaw Foundation, which intends to help save the lives of Ukrainian defenders and provide relief to as many civilians as possible: https://macpaw.foundation/.
• We are committed to our veterans
  Our Veteran Career and Empowerment Program is designed to ensure our veterans and active military personnel receive the recognition, support, and opportunities they deserve.
• Hybrid work model
  Whether to work remotely or at the hub is entirely up to you. If you decide to mix it, our Kyiv office, which works as a coworking space, is open around the clock. The office is supplied with UPS and Starlink for an uninterrupted work process.
• Your health always comes first
  We guarantee medical insurance starting on your first working month. For those abroad, you can receive a yearly Medical insurance allowance as compensation for managing your medical expenses.
• Flexible working hours
  You can choose a schedule that is comfortable for you. No one here tracks your clock in/out because MacPaw is built on trust and cooperation.
• Space to grow both professionally and personally
  Education opportunities to grow both hard and soft skills, annual development reviews, and internal community.
• Teams we are proud of
  We build honest, transparent, and reliable relationships within teams. Every Macpawian can improve processes and implement their ideas. We encourage open and constructive feedback and provide training for Macpawians on giving and receiving feedback.
• Office designed for people (and pets)
  Our office has it all: a spacious workplace with enough room for sitting up, lying down, and running around; a gym for recreation; cozy kitchens; a sleeping/meditation room; and a terrace with a view where we throw summer parties. Also, we have two cats living in the office, and you are welcome to bring your pets to the office (we have separate floors for cats and dogs).
• Time-off policy that covers life’s needs
  Convenient personal time-off policy to help you take care of essential matters in your personal life, and parental leaves. On top of all that, sabbaticals are open after 5 years of being with MacPaw.
• Join social initiatives with MacPawCares
  MacPaw participates in numerous humanitarian aid and charity projects across many fields, and you are welcome to jump in to make the world a better place.
• We’re an equal-opportunity employer. Here is a safe place for applicants of all backgrounds
  We are hiring talented humans. Meaning with all our variety of backgrounds and identities, including service members and veterans, women, members of the LGBTQIA+ community, individuals with disabilities, and other often underrepresented groups. MacPaw does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
  
  *Some benefits are under development, and new adjustments are possible.

We are seeking a highly skilled and visionary AI Tech Lead with expertise in Computer Vision and a strong focus on deploying AI solutions on edge devices. The ideal candidate will lead a team of engineers and researchers to design, develop, and implement cutting-edge AI-powered Computer Vision solutions that run efficiently on edge hardware. This role is pivotal in driving innovation and delivering scalable, real-time AI applications for our business and clients.

Key Responsibilities:

• Lead the development and deployment of Computer Vision models tailored for edge devices, ensuring high performance and low latency.
• Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define requirements and deliver robust AI solutions.
• Research and stay up-to-date with advancements in edge computing, computer vision algorithms, and AI frameworks to ensure our solutions remain cutting-edge.
• Optimize machine learning models for inference on edge devices by leveraging techniques such as quantization, pruning, and knowledge distillation.
• Mentor and guide a team of AI engineers and researchers, fostering a culture of innovation and technical excellence.

• Participate in strategic decision-making to align AI initiatives with business goals and objectives.

   

  Experience:

• Proven experience in computer vision, with a focus on deploying solutions on edge devices.
• Hands-on experience with frameworks such as TensorFlow Lite, ONNX Runtime, PyTorch Mobile, or similar.
• Strong understanding of edge AI hardware (e.g., NVIDIA Jetson, Google Coral, Qualcomm AI Engine) will be a plus

• Expertise in optimizing deep learning models for low power and memory-constrained environments.

   

  Technical Skills:

• Proficiency in programming languages like Python (C++ will be a plus)
• Strong knowledge of Computer Vision techniques, including object detection, image segmentation, and feature extraction.
• Familiarity with tools and technologies for model compression, such as TensorRT, OpenVINO, or CoreML.

• Experience with real-time data processing and streaming on edge devices.

   

  Leadership Skills:

• Demonstrated ability to lead and mentor technical teams.
• Excellent problem-solving and decision-making skills.
• Strong communication skills to convey complex technical concepts to non-technical stakeholders.

With us you will enjoy:

• Working with a team of people to build the future of an industry.
• Non-trivial challenges and various specter of interesting tasks.
• A flexible, friendly and collaborative work environment.
• Corporate culture based on common sense.
• Opportunities to influence the creation of new products and their quality.

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 seeking an AI Engineer to join one of our customers’ teams. This position will play a key role in applying state-of-the-art machine learning and AI techniques to enhance automated accessibility testing, drive intelligent analysis of scan results, and develop algorithms that add value to their product suite. The AI Engineer will work to build scalable ML systems that integrate into the client's core products, ensuring they are robust, ethical, and aligned with the client’s mission of digital equality.

The ideal candidate would have experience deploying ML models in production environments, preferably in the domains of computer vision, and NLP. An understanding of supervised and unsupervised learning, model evaluation, data science, and responsible AI principles is essential. Prior work in accessibility or web technologies is a plus.
 

Requirements:
 

• 3+ years of experience in machine learning or AI engineering, with a strong focus on deploying models in production environments.
• Proficiency with Python and common ML libraries such as TensorFlow, PyTorch, Scikit-learn, or Hugging Face Transformers.
• Experience building and maintaining scalable ML infrastructure
• Strong back-end engineering skills, including designing APIs, integrating with cloud services, and building infrastructure to support ML workflows.
• Hands-on experience with data engineering tools and workflows (e.g., AWS Glue, Athena, Spark, or similar).
• Strong understanding of model lifecycle management, including training, evaluation, deployment, and monitoring in real-world systems.
• Familiarity with web technologies (HTML, CSS, JavaScript) and an interest in digital accessibility.
• Excellent communication skills, with the ability to explain complex ML concepts to both technical and non-technical audiences.

• At least Upper Intermediate English level.

   

Nice to Have

• Computer Vision, NLP.
• Docker & AWS.
• Accessibility knowledge.
   

Responsibilities:
 

• Process and collect data for AI systems, create and maintain data pipelines for developing and deploying AI algorithms at scale.
• Research the state of the art in AI/ML and creatively apply it to our mission of digital equality.
• Design and develop algorithms using AI/ML to enhance our product suite and increase automation.
• Contribute to technical documentation and share findings with stakeholders through demos, presentations, and reports.
• Evaluate algorithm performance using rigorous statistical and domain-relevant metrics, iterating for continual improvement.
• Participate in code reviews, team planning, and cross-functional collaborations to ensure high engineering standards.
   

We offer:
 

• Annual paid vacation of 18 working days.
• Extra vacation days for long-lasting cooperation.
• Annual paid sick leave of 10 days.
• Maternity/Paternity leave.
• The opportunity for sabbatical leave.
• Marriage and Parenthood Package.
• Compensation for sports activities (up to 250$ per year) or health insurance covering (70%) — after the trial period.
• Internal education (corporate library, Udemy courses).
• Career development plan.
• English and Spanish classes.
• Paying taxes and managing PE (Private Entrepreneur).
• Technical equipment.
• Internal Referral program.
• Opportunity to take part in company volunteering activities.
• Sombra is a “Friendly to Veterans” award-holder.
  
   

If you believe you are a suitable candidate for this position, please attach your updated resume using the provided link.
Our recruitment team will review your profile, and if it aligns with our current job openings, we will contact you shortly. If you don’t receive a reply from us within 5 business days, it means we have decided to move forward with other candidates.
Thank you for understanding.

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

• Bachelor’s or Master’s 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.

Automat-it is where high-growth startups turn when they need to move faster, scale smarter, and make the most of the cloud. As an AWS Premier Partner and Strategic Partner, we deliver hands-on DevOps and FinOps and GenAI support that drives real results.

We work across EMEA and the US, fueling innovation and solving complex challenges daily. Join us to grow your skills, shape bold ideas, and help build the future of tech.

We seek an experienced Senior AI Engineer to join our team. You will work hands-on with innovative startups' Data Science and R&D teams and be in charge of various projects. You will develop robust MLOps pipelines, create cutting-edge Generative AI solutions, implement the latest technologies, and ensure the customers’ success by overseeing the project from inception to completion.

📍 Work location - remote from Ukraine

If you are interested in this opportunity, please submit your CV in English.

Responsibilities:

• Design, build, and deploy GenAI systems using LLMs for real-world applications, including agentic workflows, RAG pipelines, and orchestration logic.
• Implement multi-step reasoning systems using frameworks like LangChain, LangGraph, Strands Agents, CrewAI, and Bedrock Agents.
• Optimize retrieval pipelines with efficient embedding strategies and vector stores such as OpenSearch, PostgreSQL pgvector, Pinecone, and others.
• Rapidly experiment with and integrate new research and GenAI tooling into scalable prototypes and customer-ready solutions.
• Collaborate with cross-functional teams to ship AI-powered features and assist in aligning AI efforts with business goals.

Requirements:

• 3+ years of experience in AI/ML engineering with a track record of building and shipping production-grade AI systems.
• 5+ years of hands-on experience with Python and deep learning frameworks such as PyTorch and HuggingFace Transformers.
• Experience with orchestration frameworks such as LangChain, LangGraph, Strands Agents, CrewAI, and Bedrock Agents.
• Solid understanding of embedding strategies, retrieval optimization, and semantic search using vector stores.
• Experience with AWS services, including Bedrock, SageMaker, Lambda, and other serverless and container-based deployment approaches.
• Familiarity with MLOps practices, including CI/CD for models, monitoring, and reproducibility in cloud-native environments.
• Strong communication skills and the ability to collaborate across product and engineering teams.
• Fluent written and verbal communication skills in English

Benefits

• Professional training and certifications covered by the company (AWS, FinOps, Kubernetes, etc.)
• International work environment
• Referral program – enjoy cooperation with your colleagues and get a bonus 
• Company events and social gatherings (happy hours, team events, knowledge sharing, etc.)
• English classes
• Soft skills training

Country-specific benefits will be discussed during the hiring process.

Automat-it is committed to fostering a workplace that promotes equal opportunities for all and believes that a diverse workforce is crucial to our success. Our recruitment decisions are based on your experience and skills, recognising the value you bring to our team.

This is a fantastic opportunity to join a fast-growing company at the heart of the digital revolution. Our software product is revolutionising manufacturing through automation. We are trusted by global brands and work across sectors (mobility, consumer goods, machinery etc).

We have a talented and ambitious team. We value integrity and are passionate about our mission to revolutionise advanced manufacturing.

This is your opportunity to:

• Be part of a fast-growing software product company in advanced manufacturing.
• Learn and fulfil your potential in an open, knowledge-driven culture.
• Share in our ambitious vision and make a meaningful difference towards autonomous manufacturing.

Responsibilities: 

• Develop, test, and deploy machine learning models and algorithms for various applications. 
• Design and implement end-to-end AI solutions that integrate with existing systems. 
• Collaborate with data scientists, software engineers, and product teams to understand business needs and translate them into technical requirements. 
• Optimize and scale AI models for performance, accuracy, and sustainability. 
• Research emerging AI trends and techniques to continually improve the AI solution offerings. 
• Prepare and maintain documentation on design, code, and processes to ensure organizational knowledge retention. 
• Monitor and evaluate the performance of AI systems in production, identifying areas for improvement or further development.

You will be joining a well-versed team if you have:

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Data Science, or a related field. 
• Proven experience in developing machine learning models and deploying AI solutions. 
• Strong programming skills in languages such as Python, Java, or C++.
• Proficiency with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). 
• Experience with data processing frameworks and tools (e.g., Pandas, NumPy) and familiarity with databases (SQL, NoSQL). 
• Solid understanding of deep learning, NLP, computer vision, or other specialized areas within AI is a plus. 
• Experience with cloud platforms (AWS, Google Cloud, Azure) and containerization (Docker, Kubernetes) is beneficial. 
• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
• Good communication skills and the ability to translate complex technical concepts to non-technical stakeholders. 
• Commitment to continuous learning and development in the field of AI and emerging technologies.

Impulse is a brain training app that helps people keep their brains sharp with bite-sized fun games and logic puzzles. Impulse is the world’s most downloaded app in the Brain Training category with over 100 million downloads. The app is trusted by users worldwide, with a 4.7 rating on the App Store, and has been featured as App of the Day in over 50 countries, including the UK, Canada, and Australia.

Impulse is a part of Headway Inc, a global tech company that revolutionises lifelong learning by creating digital products for over 150 million users worldwide. Our mission is to help people grow. We’re proud to be ranked 4th among the World’s Top EdTech Сompanies by TIME magazine.

The core of our achievements is our team. That’s why, together with Tetiana, Creative & Production Lead at Impulse, we’re looking for a Junior Creative AI Specialist to join our team of superstars.
 

This job is perfect for you if you want to:

• Work alongside a team of energetic, like-minded experts. You’ll brainstorm, test ideas, and share knowledge across departments — all shoulder to shoulder with people who love what they do.
• Dive deeper into the world of creative marketing and grow fast in this field. This role is just your starting point
• Make a real impact on the performance of a #1 product in its niche. You’ll come up with creative ideas and actually see the difference your work makes.

What you will do:

• Create attention-grabbing visuals, copy, and videos with AI tools.
• Staying on top of the latest AI tools for marketing and creatives.
• Share AI tips and tricks with the team.
• Create a prompt base and applying prompt engineering for the best results from AI.
• Automate routine tasks and put the boring stuff on autopilot — from refreshes and variations to copy, voiceovers, and beyond.

What do you need to join us:

• English at Upper-intermediate level or higher.
• Hands-on experience with core AI tools such as ChatGPT and Sora.
• A passion for discovering what’s possible with AI.
• A perfect mix of creativity and analytical skills.
• Willingness and motivation to learn and grow fast.
• Interest in tracking content trends and best-performing ad practices on social media.
• A logical and structured approach to tasks, and openness to discussing ideas.
• Alignment with the values of our team (more about us - here).

Will be a plus:

• Holding a certificate proving English language proficiency (e.g., IELTS, TOEFL, etc.)
• Experience with market research and competitor analysis tools (AppMagic, FB Ad Library, TikTok Creative Center).
• Good understanding of marketing metrics and the marketing funnel.
• Basic Figma skills.
• Copywriting chops.

What do we offer:

• Work within an ambitious team on a socially impactful education product.
• An office with a reliable shelter, generators, satellite internet, and other amenities.
• Access to our corporate knowledge base and professional communities.
• Personal development plan.
• Compensation for English language learning, external training, and courses.
• Medical insurance and full sick leave compensation.
• Sports activities: running, yoga, boxing, and more.
• Corporate holidays.
• Supporting initiatives that help Ukraine. Find out more about our projects here.

Working schedule

This is a full-time position with a hybrid option. It means that we will prefer you to attend office 2-3 times per week.

Are you interested?
Send your CV!

About us:
Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with uniting top AI talents and organizing the first Data Science tech conference in Kyiv. Over the past 9 years, we have diligently fostered one of the largest Data Science & 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 looking for an MLOps Engineer specializing in Large Language Model (LLM) infrastructure to design and maintain the robust platform on which the AI models are developed, deployed, and monitored. As an MLOps Engineer, you will build the backbone of the machine learning operations – from scalable training pipelines to
Reliable deployment systems – ensuring that the NLP models (including LLMs) can be trained on large datasets and served to end-users efficiently.

This role sits at the intersection of software engineering, DevOps, and machine learning, and is crucial for accelerating the R&D in the Ukrainian LLM project. You’ll work closely with data scientists and software engineers to implement best-in-class infrastructure and workflows for the continuous delivery of AI innovations.

Requirements:
Experience & Background:
- 4+ years of experience in DevOps, MLOps, or ML Infrastructure roles.
- Strong foundation in software engineering and DevOps principles as they apply to machine learning.
- A Bachelor’s or Master’s in Computer Science, Engineering, or a related field is preferred.
Cloud & Infrastructure:
- Extensive experience with cloud platforms (AWS, GCP, or Azure) and designing cloud-native applications for ML.
- Comfortable using cloud services for compute (EC2, GCP Compute, Azure VMs), storage (S3, Cloud Storage), container registry, and serverless components where appropriate.
- Experience managing infrastructure with Infrastructure-as-Code tools like Terraform or CloudFormation.
Containerization & Orchestration:
- Proficiency in container technologies (Docker) and orchestration with Kubernetes.
- Ability to deploy, scale, and manage complex applications on Kubernetes clusters; experience with tools like Helm for Kubernetes package management.
- Knowledge of container security and networking basics in distributed systems.
CI/CD & Automation:
- Strong experience implementing CI/CD pipelines for ML projects.
- Familiar with tools like Jenkins, GitLab CI, or GitHub Actions for automating testing and deployment of ML code and models.
- Experience with specialized ML CI/CD (e.g., TensorFlow Extended TFX, MLflow for model deployment) and GitOps workflows (Argo CD) is a plus.
Programming & Scripting:
- Strong coding skills in Python, with experience in writing pipelines or automation scripts related to ML tasks.
- Familiarity with shell scripting and one or more general-purpose languages (Go, Java, or C++) for infrastructure tooling.
- Ability to debug and optimize code for performance (both in data pipelines and model inference code).
ML Pipeline Knowledge:
- Solid understanding of the machine learning lifecycle and tools.
- Experience building or maintaining ML pipelines, possibly using frameworks like Kubeflow, Airflow, or custom solutions.
- Knowledge of model serving frameworks (TensorFlow Serving, TorchServe, NVIDIA Triton, or custom Flask/FastAPI servers for ML).
Monitoring & Reliability:
- Experience setting up monitoring for applications and models (using Prometheus, Grafana, CloudWatch, or similar) and implementing alerting for anomalies.
- Understanding of model performance metrics and how to track them in production (e.g., accuracy on a validation stream, response latency).
- Familiarity with concepts of A/B testing or canary deployments for model updates in production.
Security & Compliance:
- Basic understanding of security best practices in ML deployments, including data encryption, access control, and dealing with sensitive data in compliance with regulations.
- Experience implementing authentication/authorization for model endpoints and ensuring infrastructure complies with organizational security policies.
Team Collaboration:
- Excellent collaboration skills to work with cross-functional teams.
- Experience interacting with data scientists to translate model requirements into scalable infrastructure.
- Strong documentation habits for outlining system designs, runbooks for operations, and lessons learned.

Nice to have:
LLM/AI Domain Experience:
- Previous experience deploying or fine-tuning large language models or other large-scale deep learning models in production.
- Knowledge of specialized optimizations for LLMs (such as model parallelism, quantization techniques like 8-bit or 4-bit quantization, and use of libraries like DeepSpeed or Hugging Face Accelerate for efficient training) will be highly regarded.
Distributed Computing:
- Experience with distributed computing frameworks such as Ray for scaling up model training across multiple nodes.
- Familiarity with big data processing (Spark, Hadoop) and streaming data (Kafka, Flink) to support feeding data into ML systems in real time.
Data Engineering Tools:
- Some experience with data pipelines and ETL.
- Knowledge of tools like Apache Airflow, Kafka, or dbt, and how they integrate into ML pipelines.
- Understanding of data warehousing concepts (Snowflake, BigQuery) and how processed data is used for model training.
Versioning & Experiment Tracking:
- Experience with ML experiment tracking and model registry tools (e.g., MLflow, Weights & Biases, DVC).
- Ensuring that every model version and experiment is logged and reproducible for auditing and improvement cycles.
Vector Databases & Retrieval:
- Familiarity with vector databases (Pinecone, Weaviate, FAISS) and retrieval systems used in conjunction with LLMs for augmented generation is a plus.
High-Performance Computing:
- Exposure to HPC environments or on-prem GPU clusters for training large models.
- Understanding of how to maximize GPU utilization, manage job scheduling (with tools like Slurm or Kubernetes operators for ML), and profile model performance to remove bottlenecks.
Continuous Learning:
- Up-to-date with the latest developments in MLOps and LLMOps (Large Model Ops).
- Active interest in new tools or frameworks in the MLOps ecosystem (e.g., model optimization libraries, new orchestration tools) and a drive to evaluate and introduce them to improve the processes.

Responsibilities:
- Design and implement modern, scalable ML infrastructure (cloud-native or on-premises) to support both experimentation and production deployment of NLP/LLM models. This includes setting up systems for distributed model training (leveraging GPUs or TPUs across multiple nodes) and high-throughput model serving (APIs, microservices).
- Develop end-to-end pipelines for model training, validation, and deployment.
- Automate the ML workflow from data ingestion and feature processing to model training and evaluation, using technologies like Docker and CI/CD pipelines to ensure reproducibility and reliability.
- Collaborate with Data Scientists and ML Engineers to design MLOps solutions that meet model performance and latency requirements.
- Architect deployment patterns (batch, real-time, streaming inference) appropriate for various use-cases (e.g., a real-time chatbot vs. offline analysis).
- Implement and uphold best practices in MLOps, including automated testing of ML code, continuous integration/continuous deployment for model updates, and rigorous version control for code, data, and model artifacts.
- Ensure every model and dataset is properly versioned and reproducible.
- Set up monitoring and alerting for deployed models and data pipelines.
- Use tools to track model performance (latency, throughput) and accuracy drift in production.
- Implement logging and observability frameworks to quickly detect anomalies or degradations in model outputs.
- Manage and optimize our Kubernetes-based deployment environments. Containerize ML services and use orchestration (Kubernetes, Docker Swarm, or similar) to scale model serving infrastructure.
- Handle cluster provisioning, health, and upgrades, possibly using Helm charts for managing LLM services.
- Maintain infrastructure-as-code (e.g., Terraform, Ansible) for provisioning cloud resources and ML infrastructure, enabling reproducible and auditable changes to the environment.
- Ensure the infrastructure is scalable, cost-effective, and secure.
- Perform code reviews and guide other engineers (both MLOps and ML developers) on building efficient and maintainable pipelines.
- Troubleshoot issues across the ML lifecycle, from data processing bottlenecks to model deployment failures, and continuously improve system robustness.

The company offers:
- Competitive salary.
- Equity options in a fast-growing AI company.
- Remote-friendly work culture.
- Opportunity to shape a product at the intersection of AI and human productivity.
- Work with a passionate, senior team building cutting-edge tech for real-world business use.

We're looking for an MLOps Engineer to join a high-impact healthcare initiative with our client, a world-renowned leader in medical technology. You’ll be part of a team driving the cloud migration of a secure digital surgical ecosystem from Azure to AWS.

This platform is at the heart of a next-generation surgical experience, connecting data, devices, and teams to power advanced analytics and machine learning models. You will be responsible for building, automating, and maintaining the infrastructure that supports the entire machine learning lifecycle, from data ingestion to model deployment and monitoring. In this role, you'll help build a secure, resilient, and compliant environment for critical healthcare applications that leverage AI and machine learning.

Required Skills

• MLOps Expertise: Proven experience in building and managing machine learning pipelines in a production environment.
• AWS Expertise: Extensive hands-on experience with core AWS services (S3, SageMaker, EKS, Lambda, CloudFormation, etc.).
• DevOps Practices: Deep understanding of CI/CD, automation, and infrastructure as code (IaC) using Terraform or CloudFormation.
• Containerization: Solid experience with Docker and Kubernetes for orchestrating ML workloads.
• Scripting: Proficiency in Python and other scripting languages for automation.
• Data Engineering: Familiarity with data processing workflows and tools for handling large datasets.

Nice-to-Have Skills

• Media Experience: Experience with AWS Media Services (e.g., AWS Elemental, Kinesis Video Streams) or a background in managing video data.
• Surgical/Medical Context: Prior experience with medical devices, DICOM standards, or healthcare data is a plus.
• Machine Learning Frameworks: Familiarity with frameworks like TensorFlow, PyTorch, or scikit-learn.

Job Responsibilities

This is your chance to work on a product that impacts lives, leverages modern cloud technology, and prioritizes security, performance, and reliability.

Key Responsibilities

• Design and implement MLOps pipelines for the training, testing, and deployment of machine learning models on AWS.
• Automate the end-to-end machine learning lifecycle, including data versioning, model training, and continuous integration/continuous delivery (CI/CD) for model updates.
• Manage and optimize the cloud infrastructure on AWS to ensure scalable and cost-effective model serving and inference.
• Collaborate with data scientists and machine learning engineers to streamline the transition of models from development to production.
• Establish robust monitoring and logging for model performance, data drift, and system health in a production environment.
• Ensure the security and compliance of the ML platform, adhering to healthcare industry standards.
• Provide technical leadership and guidance on MLOps best practices, tools, and workflows.

Department/Project Description

Join us to build the connected vision intelligence layer that unifies surgical imaging, robotics, and data services across the operating room portfolio spanning endoluminal, orthopedics, and the next-gen general-surgery platform, while powering the digital ecosystem in hospitals. You’ll help transform raw surgical video and device signals into real-time insights, collaborative telepresence, and longitudinal case intelligence used before, during, and after procedures. First product releases include surgical video editing/publishing and telepresence, rolling out to select sites in the near future. Your work will directly accelerate that journey and connect robotic vision to the OR and hospital digital platform

This platform is at the heart of a next-generation surgical experience – designed to connect data, devices, and teams. The current release includes tools for surgical video management, telepresence, and case planning, already rolled out in select hospitals.

This is a fantastic opportunity to join a fast-growing company at the heart of the digital revolution. Our software product is revolutionising manufacturing through automation. We are trusted by global brands and work across sectors (mobility, consumer goods, machinery etc).

We have a talented and ambitious team. We value integrity and are passionate about our mission to revolutionise advanced manufacturing.

This is your opportunity to:

• Be part of a fast-growing software product company in advanced manufacturing.
• Learn and fulfil your potential in an open, knowledge-driven culture.
• Share in our ambitious vision and make a meaningful difference towards autonomous manufacturing.

Responsibilities: 

• Develop, test, and deploy machine learning models and algorithms for various applications. 
• Design and implement end-to-end AI solutions that integrate with existing systems. 
• Collaborate with data scientists, software engineers, and product teams to understand business needs and translate them into technical requirements. 
• Optimize and scale AI models for performance, accuracy, and sustainability. 
• Research emerging AI trends and techniques to continually improve the AI solution offerings. 
• Prepare and maintain documentation on design, code, and processes to ensure organizational knowledge retention. 
• Monitor and evaluate the performance of AI systems in production, identifying areas for improvement or further development.

You will be joining a well-versed team if you have:

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Data Science, or a related field. 
• Proven experience in developing machine learning models and deploying AI solutions. 
• Strong programming skills in languages such as Python, Java, or C++.
• Proficiency with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). 
• Experience with data processing frameworks and tools (e.g., Pandas, NumPy) and familiarity with databases (SQL, NoSQL). 
• Solid understanding of deep learning, NLP, computer vision, or other specialized areas within AI is a plus. 
• Experience with cloud platforms (AWS, Google Cloud, Azure) and containerization (Docker, Kubernetes) is beneficial. 
• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
• Good communication skills and the ability to translate complex technical concepts to non-technical stakeholders. 
• Commitment to continuous learning and development in the field of AI and emerging technologies.

About the project:

We are building a corporate AI Assistant powered by Microsoft Azure and OpenAI technologies. The system helps employees search, analyze, and generate internal documents. The long-term goal is to extend AI Assistant capabilities across all company departments.

To strengthen our team, we are looking for an experienced ML Architect (Azure AI / RAG) who will design and implement the machine learning architecture, integrate AI models, and ensure production-level performance and reliability.

Responsibilities:

• Design and implement AI architecture on Microsoft Azure (Azure ML, Cognitive Search, OpenAI, Databricks). 
• Build and manage RAG pipelines (Retrieval-Augmented Generation) and vector search systems. 
• Develop and optimize ML pipelines for embeddings, data preprocessing, and model evaluation. 
• Collaborate with DevOps and Data Engineer teams to ensure seamless integration and deployment. 
• Establish and maintain MLOps practices (model versioning, evaluation, monitoring). 
• Define and track AI performance metrics (latency, precision, recall, cost per request). 
• Create documentation (ADR, architecture diagrams, experiment tracking).

Requirements:

• 3+ years of experience in Machine Learning / AI / Data Engineering. 
• Strong background with Microsoft Azure ML / Cognitive Search / Databricks / OpenAI. 
• Proficiency in Python, FastAPI, LangChain / LlamaIndex, MLflow, Airflow. 
• Hands-on experience with vector databases (FAISS, Pinecone, pgvector, Cognitive Search). 
• Understanding of RAG, embeddings, prompt optimization, LLM orchestration. 
• Experience building MLOps / CI-CD for ML models in production. 
• English — Upper-Intermediate+ (for documentation and collaboration).

Will be a plus:

• Experience with Azure OpenAI Service, Azure Document Intelligence. 
• Knowledge of data governance, PII protection, cost optimization. 
• Background in AI-driven enterprise automation or corporate assistants.

We offer:

• Opportunity to design a core AI architecture from scratch and influence all key technical decisions. 
• Participation in a high-impact AI transformation project that scales across multiple departments. 
• Remote or hybrid work format, flexible schedule. 
• Transparent B2B / contract cooperation. 
• Supportive and technically strong team (DevOps, Data, Product).

How to apply:

Send your CV.
We will contact you shortly.

Position overview

We are seeking a highly skilled AI & ML Engineer to join our innovative team. In this role, you will lead the development, optimization, and deployment of advanced machine learning and artificial intelligence models. You will drive state-of-the-art research, build scalable pipelines, and collaborate with cross-functional teams to translate business needs into effective ML solutions.

This position offers the opportunity to work on cutting-edge technologies in a dynamic, fast-paced environment, contributing to impactful projects that power next-generation AI applications.

Responsibilities

• Design, implement, and optimize machine learning and AI models, including classification, regression, clustering, and agent tuning.
• Experiment with the latest methods, frameworks, and architectures to enhance model performance and efficiency.
• Develop robust, scalable ML pipelines for training, validation, and inference.
• Deploy ML models into production environments (cloud or on-prem), ensuring high reliability, low latency, and scalability.
• Apply MLOps best practices including CI/CD, monitoring, automated retraining, and model registry management.
• Partner with data engineering teams to source, clean, and transform large datasets for model training and inference.
• Ensure high data quality, perform feature engineering, and support real-time data integration processes.
• Work closely with data scientists, software engineers, and product managers to align ML solutions with business goals.
• Clearly communicate complex technical results to both technical and non-technical stakeholders.
• Provide technical guidance and mentorship to junior ML engineers and data scientists.
• Contribute to establishing team best practices, code reviews, and architectural decisions.

Requirements

• 5+ years of professional experience in machine learning, AI engineering, or related fields.
• Master’s degree in Computer Science, Machine Learning, Physics, or related field; PhD preferred.
• Proficient in Python and ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Strong understanding of algorithms, statistics, probability, and linear algebra.
• Hands-on experience with data pipelines and ETL tools (e.g., Spark, AWS Lambda, AWS Glue).
• Practical experience with cloud platforms, preferably AWS.
• Solid software engineering fundamentals including version control (Git), testing, and design patterns.
• Demonstrated success in deploying ML models into production at scale.
• Familiarity with MLOps tools such as MLflow, Kubeflow, SageMaker, or Vertex AI.
• Excellent analytical, problem-solving, and communication skills.
• Ability to work autonomously and collaboratively within a fast-paced, cross-functional team environment.

Nice to have

• Experience with agentic frameworks like LangChain or LangGraph

Client

Our client is a leading Fortune 500 financial technology company that provides comprehensive payment solutions and financial services across multiple continents. They process billions of transactions annually and serve millions of customers worldwide.

You'll collaborate with a world-class team of senior data scientists, ML engineers, and technology consultants from leading organizations in the fintech and cloud computing space. This diverse group brings together deep technical expertise, industry knowledge, and proven experience delivering mission-critical solutions at enterprise scale.

Position overview

We are seeking an experienced Senior MLOps Engineers with deep expertise in Generative AI implementations. This role is designed for seasoned ML engineering professionals who have successfully transitioned their expertise into production GenAI environments - not for those simply exploring AI technologies.

Technology stack

AWS Bedrock, SageMaker, and comprehensive AI/ML service ecosystem
Vector databases and advanced RAG architectures
Enterprise-scale data processing and real-time model deployment systems
Automated CI/CD pipelines specifically designed for ML workflows

Responsibilities

• Design and implement robust MLOps pipelines for GenAI solutions using AWS Bedrock platform
• Lead the selection, training, and fine-tuning of Foundation Models (FM) and Large Language Models (LLM) for specific business use cases
• Architect and deploy RAG (Retrieval-Augmented Generation) systems with vector databases
• Develop and optimize prompt engineering strategies for production environments
• Integrate AI-powered chatbots and conversational interfaces into existing business workflows
• Implement comprehensive automation frameworks across the AI/ML lifecycle
• Manage diverse data sources and ensure optimal data preparation for AI platform consumption
• Scale proof-of-concepts to production-ready, enterprise-grade solutions

Requirements

• Hands-on, production-level experience with implementation and management
• Proven experience selecting, training, and fine-tuning Foundation Models (FM) or Large Language Models (LLM) for specific business use cases
• Deep hands-on knowledge of Retrieval-Augmented Generation implementation and vector database management
• Advanced skills in designing and optimizing prompt engineering strategies for production AI applications
• Demonstrated experience integrating and deploying chatbots within business workflows and implementing AI automation frameworks
• Expert understanding of diverse data types (structured, semi-structured, unstructured) and their utilization within AI platforms
• Proven track record of transitioning POCs to production-ready, enterprise-scale solutions
• Strong AWS cloud services background and advanced Python skills with ML frameworks (TensorFlow, PyTorch, etc.)
• ML engineering/MLOps experience with 2+ years dedicated GenAI production experience
• To collaborate with onsite team during US Eastern Time (ET) business hours

Nice to have

• Bachelor's degree in Computer Science, Data Science, Engineering, or related technical field (Master's preferred)
• AWS certifications (Machine Learning Specialty, Solutions Architect, etc.)
• Experience with financial services or payment processing systems

Position overview

DataArt is a global software engineering firm and a trusted technology partner for market leaders and visionaries. Our world-class team designs and engineers data-driven, cloud-native solutions to deliver immediate and enduring business value.

We promote a culture of radical respect, prioritizing your personal well-being as much as your expertise. We stand firmly against prejudice and inequality, valuing each of our employees equally.

We respect the autonomy of others before all else, offering remote, onsite, and hybrid work options. Our Learning and development centers, R&D labs, and mentorship programs encourage professional growth.

Our long-term approach to collaboration with clients and colleagues alike focuses on building partnerships that extend beyond one-off projects. We provide the ability to switch between projects and technology stacks, creating opportunities for exploration through our learning and networking systems to advance your career.

We are looking for a Senior Machine Learning Engineer to design, develop, and deploy advanced ML models focused on betting position forecasting, real-time analytics, and anomaly detection. The ideal candidate will have strong expertise in time series forecasting, predictive modeling, and scalable production deployment. You will work closely with cross-functional teams to integrate machine learning solutions that drive data-driven decision-making in a fast-paced betting environment, ensuring high model accuracy and reliability.

Responsibilities

• Design and develop machine learning models for betting position forecasting and recommendation systems
• Build and deploy predictive analytics solutions delivering real-time betting insights
• Implement anomaly detection systems to identify unusual betting patterns and potential risks
• Develop pattern recognition algorithms for market trend analysis and user behavior prediction
• Ensure scalable, reliable deployment of ML models within production betting environments
• Monitor, evaluate, and optimize model performance and accuracy continuously
• Collaborate closely with development teams to integrate ML solutions into betting platforms

Requirements

• Strong proficiency in Python and core ML libraries (e.g., scikit-learn, TensorFlow, PyTorch)
• Proven experience in time series forecasting, predictive modeling, and anomaly detection
• Solid grasp of statistical analysis and probability theory relevant to betting/gaming contexts
• Hands-on experience deploying ML models in real-time production environments
• Expertise in data preprocessing, feature engineering, and model validation techniques
• Familiarity with ML Ops best practices including model monitoring and versioning

Nice to have

• Experience with Azure ML or similar cloud ML platforms
• Knowledge of databases, data pipelines, and data engineering fundamentals
• Understanding of A/B testing and experimentation frameworks
• Experience with containerization tools like Docker and CI/CD pipelines