Jobs

We are looking for a Data Scientist to work on customer-facing projects, combining advanced data science techniques with machine learning and big data technologies to design and implement solutions that meet specific customer needs and business objectives. 

Requirements:

• 2+ years data science experience
• BSc or equivalent in Mathematics, Statistics, Computer Science, Economics, or related field 
• Proficient in Apache Spark, Python/PySpark, and SQL
• Experience with Hadoop ecosystem (Hive, Impala, HDFS, Sqoop) and pipeline optimization
• Hands-on experience with AI agents and LLMs
• Strong ML feature engineering and financial analytics skills
• Experience with workflow tools (Airflow, MLflow, n8n) and Git
• Customer-facing and team training abilities

• Fluent English

   

Responsibilities:

• Deploy solutions and manage pilots
• Design customer-specific technical solutions across project lifecycle
• Lead data science teams and technical partnerships
• Engineer features from diverse data sources
• Extract insights and investigate anomalies in big data
• Build technical relationships with customers and partners
• Provide product requirements to management
• Train customers on system usage and monitoring. 

Recruitment process:

• Screening call  (20 min)
• Technical Interview with Team Lead (60 min)
• Technical Test (2 hours take-home assignment)
• Interview with Global Head of Data(30 min)
• Interview with VP of R&D Manager (30 min)
• HR Interview (30 min)

• Reference Checks

   

Timeline: Complete process typically takes 2-3 weeks from application to offer.

We offer:

• Competitive compensation based on your skills and experience
• 24 days of annual paid vacation and 5 sick leaves
• Exciting projects involving the newest technologies
• Accounting as a service
• Flexible working hours
• Long-term employment 

Hi there!
At Slotsense, we’re reshaping the iGaming experience using cutting-edge AI technologies. Our mission is to build intelligent, human-like chat experiences that elevate engagement and personalization. We’re looking for a highly skilled AI Expert to take our GPT-powered chatbot to the next level.

You’ll be at the core of our AI system — designing agentic workflows, building and refining AI agents, crafting advanced prompts, and implementing modern techniques like RAG, Langchain, and LLMOps. Strong Python skills are also essential for success in this role.

What you’ll do:
• Design and implement advanced AI workflows and agent-based architectures
• Apply and fine-tune RAG (Retrieval-Augmented Generation) pipelines
• Craft high-quality prompts and experiment with prompt engineering strategies
• Work with Langchain and other LLMOps tools to optimize chatbot performance
• Analyze user behavior to improve system accuracy and naturalness
• Collaborate closely with engineers and product teams to test and deploy improvements
• Stay ahead of trends in LLMs and conversational AI

What we’re looking for:
• Proven experience with GPT or other large language models
• Hands-on experience building AI agents and agentic workflows
• Deep understanding of RAG and its real-world implementation
• Strong Python skills and familiarity with vector databases
• Experience with Langchain and LLMOps best practices
• Excellent English skills for prompt writing and collaboration
• Analytical mindset and proactive approach to experimentation
• Passion for AI and continuous learning

We are seeking a highly skilled Machine Learning (ML) Tech Lead with a strong background in Large Language Models (LLMs) and AWS Cloud services. The ideal candidate will oversee the development and deployment of cutting-edge AI solutions while managing a team of 5-10 engineers. This leadership role demands hands-on technical expertise, strategic planning, and team management capabilities to deliver innovative products at scale.
 

Responsibilities:

• Leadership & Management
  -Lead and manage a team of 5-10 engineers, providing mentorship and fostering a collaborative team environment;
  -Drive the roadmap for machine learning projects aligned with business goals;
  -Coordinate cross-functional efforts with product, data, and engineering teams to ensure seamless delivery.
• Machine Learning & LLM Expertise
  -Design, develop, and fine-tune LLMs and other machine learning models to solve business problems;
  -Evaluate and implement state-of-the-art LLM techniques for NLP tasks such as text generation, summarization, and entity extraction;
  -Stay ahead of advancements in LLMs and apply emerging technologies;
  -Expertise in multiple main fields of ML: NLP, Computer Vision, RL, deep learning and classical ML.
• AWS Cloud Expertise
  -Architect and manage scalable ML solutions using AWS services (e.g., SageMaker, Lambda, Bedrock, S3, ECS, ECR, etc.);
  -Optimize models and data pipelines for performance, scalability, and cost-efficiency in AWS;
  -Ensure best practices in security, monitoring, and compliance within the cloud infrastructure.
• Technical Execution
  -Oversee the entire ML lifecycle, from research and experimentation to production and maintenance;
  -Implement MLOps and LLMOps practices to streamline model deployment and CI/CD workflows;
  -Debug, troubleshoot, and optimize production ML models for performance.
• Team Development & Communication
  -Conduct regular code reviews and ensure engineering standards are upheld;
  -Facilitate professional growth and learning for the team through continuous feedback and guidance;
  -Communicate progress, challenges, and solutions to stakeholders and senior leadership.
  
  Qualifications:
• Proven experience with LLMs and NLP frameworks (e.g., Hugging Face, OpenAI, or Anthropic models);
• Strong expertise in AWS Cloud Services;
• Strong experience in ML/AI, including at least 2 years in a leadership role;
• Hands-on experience with Python, TensorFlow/PyTorch, and model optimization;
• Familiarity with MLOps tools and best practices;
• Excellent problem-solving and decision-making abilities;
• Strong communication skills and the ability to lead cross-functional teams;
• Passion for mentoring and developing engineers.

Employeer - defense tech company specializing in the development of innovative solutions in the direction of Embedded systems and radio frequency (RF) engineering.

Responsibilities:
•⁠ ⁠Develop and implement computer vision algorithms using both classical techniques and neural networks.
•⁠ ⁠Utilize and understand popular networks and their building blocks in computer vision tasks.

Requirements:
•⁠ ⁠Proven experience with classical computer vision and neural networks
•⁠ ⁠Strong understanding of geometrical computer vision principles
•⁠ ⁠Hands-on experience in implementing low-level CV algorithms
•⁠ ⁠In-depth knowledge of popular computer vision networks and components
•⁠ ⁠Ability to quickly navigate through recent research and trends in computer vision
•⁠ ⁠Proficiency in Python or C++
•⁠ ⁠Proficiency in SLAM/VIO
•⁠ ⁠Experience with Linux
•⁠ ⁠Extensive experience with common frameworks/libraries used for computer vision (OpenCV, numpy, PyTorch, ONNX, Eigen, etc.)

Working conditions:

• Full employment
• Work from the office in Kyiv or full remote
• Official employment
• Reservation from mobilization
• 24 calendar days of vacation and paid sick leave
• A dynamic, innovative and large-scale team working on a number of new products and improving current products

Lobby X is a socially responsible business, a unique combination of the job platform and full-cycle recruiting agency, specializing in hiring top talents for government, business, tech, miltech, and progressive non-governmental organizations in Ukraine and globally.

Responsibilities

Model Fine-Tuning and Deployment:

Fine-tune pre-trained models (e.g., BERT, GPT) for specific tasks and deploy them using Amazon SageMaker and Bedrock.

RAG Workflows:

Establish Retrieval-Augmented Generation (RAG) workflows that leverage knowledge bases built on Kendra or OpenSearch. This includes integrating various data sources, such as corporate documents, inspection checklists, and real-time external data feeds.

MLOps Integration:

The project includes a comprehensive MLOps framework to manage the end-to-end lifecycle of machine learning models. This includes continuous integration and delivery (CI/CD) pipelines for model training, versioning, deployment, and monitoring. Automated workflows ensure that models are kept up-to-date with the latest data and are optimized for performance in production environments.

Scalable and Customizable Solutions:

Ensure that both the template and ingestion pipelines are scalable, allowing for adjustments to meet specific customer needs and environments. This involves setting up RAG workflows, knowledge bases using Kendra/OpenSearch, and seamless integration with customer data sources.

End-to-End Workflow Automation:

Automate the end-to-end process from user input to response generation, ensuring that the solution leverages AWS services like Bedrock Agents, CloudWatch, and QuickSight for real-time monitoring and analytics.

Advanced Monitoring and Analytics:

Integrated with AWS CloudWatch, QuickSight, and other monitoring tools, the accelerator provides real-time insights into performance metrics, user interactions, and system health. This allows for continuous optimization of service delivery and rapid identification of any issues.

Model Monitoring and Maintenance:

Implement model monitoring to track performance metrics and trigger retraining as necessary.

Collaboration:

Work closely with data engineers and DevOps engineers to ensure seamless integration of models into the production pipeline.

Documentation:

Document model development processes, deployment procedures, and monitoring setups for knowledge sharing and future reference.

Must-Have Skills

Machine Learning: Strong experience with machine learning frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers.

MLOps Tools: Proficiency with Amazon SageMaker for model training, deployment, and monitoring.

Document processing: Experience with document processing for Word, PDF, images.

OCR: Experience with OCR tools like Tesseract / AWS Textract (preferred)

Programming: Proficiency in Python, including libraries such as Pandas, NumPy, and Scikit-Learn.

Model Deployment: Experience with deploying and managing machine learning models in production environments.

Version Control: Familiarity with version control systems like Git.

Automation: Experience with automating ML workflows using tools like AWS Step Functions or Apache Airflow.

Agile Methodologies: Experience working in Agile environments using tools like Jira and Confluence.

Nice-to-Have Skills

LLM: Experience with LLM / GenAI models, LLM Services (Bedrock or OpenAI), LLM abstraction like (Dify, Langchain, FlowiseAI), agent frameworks, rag.

Deep Learning: Experience with deep learning models and techniques.

Data Engineering: Basic understanding of data pipelines and ETL processes.

Containerization: Experience with Docker and Kubernetes (EKS).

Serverless Architectures: Experience with AWS Lambda and Step Functions.

Rule engine frameworks: Like Drools or similar

If you are a motivated individual with a passion for ML and a desire to contribute to a dynamic team environment, we encourage you to apply for this exciting opportunity. Join us in shaping the future of infrastructure and driving innovation in software delivery processes.

We are seeking a highly skilled Machine Learning (ML) Tech Lead with a strong background in Large Language Models (LLMs) and AWS Cloud services. The ideal candidate will oversee the development and deployment of cutting-edge AI solutions while managing a team of 5-10 engineers. This leadership role demands hands-on technical expertise, strategic planning, and team management capabilities to deliver innovative products at scale.
 

Responsibilities:

• Leadership & Management
  -Lead and manage a team of 5-10 engineers, providing mentorship and fostering a collaborative team environment;
  -Drive the roadmap for machine learning projects aligned with business goals;
  -Coordinate cross-functional efforts with product, data, and engineering teams to ensure seamless delivery.
• Machine Learning & LLM Expertise
  -Design, develop, and fine-tune LLMs and other machine learning models to solve business problems;
  -Evaluate and implement state-of-the-art LLM techniques for NLP tasks such as text generation, summarization, and entity extraction;
  -Stay ahead of advancements in LLMs and apply emerging technologies;
  -Expertise in multiple main fields of ML: NLP, Computer Vision, RL, deep learning and classical ML.
• AWS Cloud Expertise
  -Architect and manage scalable ML solutions using AWS services (e.g., SageMaker, Lambda, Bedrock, S3, ECS, ECR, etc.);
  -Optimize models and data pipelines for performance, scalability, and cost-efficiency in AWS;
  -Ensure best practices in security, monitoring, and compliance within the cloud infrastructure.
• Technical Execution
  -Oversee the entire ML lifecycle, from research and experimentation to production and maintenance;
  -Implement MLOps and LLMOps practices to streamline model deployment and CI/CD workflows;
  -Debug, troubleshoot, and optimize production ML models for performance.
• Team Development & Communication
  -Conduct regular code reviews and ensure engineering standards are upheld;
  -Facilitate professional growth and learning for the team through continuous feedback and guidance;
  -Communicate progress, challenges, and solutions to stakeholders and senior leadership.
  
  Qualifications:
• Proven experience with LLMs and NLP frameworks (e.g., Hugging Face, OpenAI, or Anthropic models);
• Strong expertise in AWS Cloud Services;
• Strong experience in ML/AI, including at least 2 years in a leadership role;
• Hands-on experience with Python, TensorFlow/PyTorch, and model optimization;
• Familiarity with MLOps tools and best practices;
• Excellent problem-solving and decision-making abilities;
• Strong communication skills and the ability to lead cross-functional teams;
• Passion for mentoring and developing engineers.

We are Onicore — fintech company specializing in developing products for cryptocurrency operations. 

Registered in the USA, our company is powered by a talented Ukrainian team, working across the globe.
 

📊 Now we’re on the hunt for a specialist who will drive the project of algorithmic trading. 

Your skills:

- 3+ years of experience in Data Science;

- excellent command of Python, understanding of the principles of OOP;

- deep knowledge in linear algebra, probability theory and mathematical statistics;

- data collection and preprocessing (numpy, pandas, scikit-learn,ta-lib);

- experience working with all types of classical machine learning (Supervised Learning, Unsupervised Learning, Reinforcement Learning);

- development experience and deep understanding of the principles of the architectures: RNN, LSTM, GRU, CNN, Transformer in the field of analysis and prediction of time sequences (time series predictions);

- confident use of both high-level and low-level APIs for TensorFlow (writing custom training loops, custom metrics & loss_functions). 

Knowledge of PyTorch is welcome;

- the ability to visualize the learning process using TensorBoard;

- boosting neural networks (Distributed XGBoost/LightGBM);

- visualization of results (matplotlib, seaborn).

Would be a plus:

- experience with currency markets;

- PhD degree in the field of data science / machine learning.

Your responsibilities:

● solving algorithmic trading problems: regression/autoregression, classification of timeseries/financial series, working with cryptocurrency quotes.

What’s in it for you? 

🏥 Health first: Comprehensive medical insurance.

🤓 Keep growing: We cover courses, conferences, training sessions, and workshops.

💪 Stay active mentally and physically : Sports / hobby / personal psychologist to fuel yourself.

💼 We've got your back: Access to legal assistance when you need it.

🧗‍♂️ Inspiring vibes: Join a motivated, goal-oriented team that supports each other.

🧑‍💻 Make a difference: Have a direct impact on shaping and growing the product.

💻 Work smarter: Corporate laptops to help you do your best work.

Join our team and help us level up!

About the Role:

As a Computer Vision Engineer, you will play a key role in our AI team, designing and building solutions that make legal collaboration seamless and accessible. You will work on a cutting-edge product that leverages computer vision and other advanced AI techniques to support the automotive industry. Our platform, SelfInspection, enables automated vehicle inspections. Users capture photos of a vehicle's exterior, interior, and tires, which are then analyzed by our AI and experts to generate detailed condition reports. The first version of the product is live, and we are actively developing its second iteration.

Responsibilities:

• Train, evaluate, and deploy computer vision models for tasks such as instance segmentation, object detection, classification, and tracking
• Improve and optimize existing computer vision models
• Prepare high-quality training datasets using annotated data provided by the annotation team
• Stay current with advancements in the computer vision field to ensure the use of efficient and modern approaches
• Collaborate with C-level stakeholders to define technical requirements and specifications for new features

Qualifications:

• Minimum of 5 years of hands-on experience in machine learning, computer vision, or a closely related field
• Proven experience in training, evaluating, and optimizing deep learning models for production environments
• Strong background in data collection, preprocessing, augmentation, and annotation workflows
• Bachelor's, Master’s, or Ph.D. degree in Computer Science, Electrical Engineering, Mathematics, or a related discipline (preferred but not required)

Skills:

• Hands-on experience with deep learning frameworks, particularly PyTorch and/or TensorFlow
• Deep understanding of convolutional neural networks (CNNs), transformers, and core computer vision tasks such as image classification, object detection, segmentation, and tracking
• Proficiency with scientific and image processing libraries such as NumPy, OpenCV, and scikit-learn
• Familiarity with model deployment techniques (e.g., ONNX, TensorRT, TorchScript, TensorFlow Lite) and performance optimization strategies
• Strong problem-solving skills and the ability to decompose complex vision tasks into modular components
• Excellent communication and collaboration skills across both technical and non-technical teams

Will be a Plus:

• Interest in prototyping and experimenting with new computer vision techniques
• Experience designing AI products from the ground up, with a solid understanding of AI system architecture

📍 Remote | Full-time
Introduct Group is an international company contributing to software development excellency in tailored solutions to our customers worldwide.
The company is originally from Estonia, with headquarters in Kyiv and offices in other countries. Introduct Tech welcomes a talented professional to join our challenging and dynamic European project in Logistics Industry.
 

Introduct Group is an international company delivering tailored software solutions to clients worldwide. Founded in Estonia, with headquarters in Kyiv and offices across several countries, we combine global vision with local expertise.

We are currently seeking a results-oriented Tableau professional to join our dynamic European project in the Logistics Industry as part of our BI Team.

This team plays a critical role in delivering business intelligence services — from maintaining analytical data warehouses to creating insightful dashboards and supporting company-wide analytics initiatives.
 

Your Role

We’re looking for a senior-level Tableau expert who will:

• Analyze existing dashboards and suggest improvements
• Have at least 3 years of experience in a similar position
• Apply best practices to enhance performance and user experience
• Ensure data integrity and consistency across reports
• Document solutions and support the team through training and knowledge sharing
• Leverage your experience in Tableau performance tuning, data modeling, and stakeholder collaboration to drive measurable improvements
• Upper-intermediate English
   

What We Offer

• Competitive salary
• Fully remote work format
• Opportunities for professional development through English courses and training programs
• A friendly and professional team environment where your contributions truly matter

If you’re passionate about turning data into insights and helping teams perform at their best — we’d love to hear from you. Join Introduct and make your impact through BI.

PIN-UP Global is an international holding specializing in the development and implementation of advanced technologies, B2B solutions and innovative products for the iGaming industry.

Our holding is represented in seven countries (Cyprus, Ukraine, Poland, Kazakhstan, Armenia, Peru, Malta). The headquarters of the holding is located in Cyprus.

We are looking for a Senior Data Scientist to join our team!

Requirements:

- Proven experience in analysis of large amount of data;

- Experience in solving customer behavior prediction tasks;

- Knowledge of ML algorithms for regression, classification, clustering, ability to apply them to business problems;

- Solid experience in SQL;

- Extensive experience with Python for data processing, modeling, and visualization;

- Deep understanding of statistics, probability theory;

- Passion to drive projects from R&D to business value.

Will be plus:

- Familiarity with AWS infrastructure and toolchain (SageMaker, CloudFormation, CloudWatch, etc.);

- Familiarity with BI tools (Metabase, Tableau);

- Experience with tools for managing ML workflows;

- Knowledge and experience with algorithms and data structures;

- Knowledge of OOP;

- Understanding of containerization technologies (Docker);

- Participation in Kaggle competitions.

Responsibilities:

- Developing and testing machine learning models for customer behavior prediction, deploying to production;

- Working with tabular data collecting, cleaning, and exploring datasets, building ML pipelines;

- Applying statistical methods to analyze and interpret data, finding patterns, insights to improve quality of models;

- Maintaining existing models;

- Communicating and presenting results.

Benefits:

🍀 An exciting and challenging job in a fast-growing product holding, the opportunity to be part of a multicultural team of top professionals in Development, Engineering and Architecture, Management, Operations, Marketing, etc;

🤝 Great working atmosphere with passionate IT experts and leaders, sharing a friendly culture and a success-driven mindset is guaranteed;

📍Beautiful offices in Limassol, Warsaw, Almaty, Yerevan — work with comfort and enjoy the opportunity to build a network of connections with IT professionals day by day;

🧑‍💻 Laptop & all necessary equipment for work according to the ecosystem standards;

🏖 Paid vacations, personal events days, days off;

🫖 Paid sick leave;

👨‍⚕ Medical insurance;

💵 Referral program — enjoy cooperation with your colleagues and get a bonus;

📚 Educational support by our L&D team: internal and external trainings and conferences, courses on Udemy;

🦄 Multiple internal activities: online platform with newsletters, quests, gamification, and presents for collecting bonuses, PIN-UP talks club for movie and book lovers, board games cozy evenings, special office days dedicated to holidays, etc;

🎳 Company events, team buildings.

The Product Data Science team at Noom (www.noom.com) is seeking a mid-level Data Scientist Contractor. The primary responsibility is to conduct product analysis and help design & evaluate A/B tests.

Noom is more than just a health-tech company — it's a mission-driven organization that has helped over 50 million users worldwide build healthier habits through science-backed behavioral psychology. Backed by $650M+ in funding and recognized by Forbes as one of America's Best Startup Employers, Noom is scaling rapidly. If you're looking to work on a product that genuinely changes lives — this is the place.
 

The Product Data Science team currently consists of 4 other Data Scientists, who work together to tackle a variety of projects each week. We sit alongside the Business Data Science team (also 4 people) and the BI Engineering team.
 

“Product” at Noom covers all their in-app programs and features (including Noom Med!), as well as our Growth efforts (i.e. how we position and price our different product offerings!). 
 

Key Responsibilities:

• Product Analysis:

  - Answer insightful analysis questions from stakeholders across the Product org

  - Be able to ramp up on how different parts of the product & our data model function, to pull accurate results

  - Partner with PMs and Engineers to design key metrics for different initiatives

• Experiment Analysis:

  - Be the “stats expert” alongside PMs to ensure we design effective experiments

  - Understand and be able to intuitively explain concepts like power & sample size

  - Analyze experiment results to determine what is statistically significant, being able to take into account common pitfalls and “p-hacking” that can happen with A/B testing

• Specific Deliverables (First 3-6 months):

  - Ramp up on a particular product area and start answering ad hoc insight questions from there

  - Design an experiment (with another Product DS there to mentor), see it launch, and then analyze it

  - Give feedback on new team processes and come up with an idea to iterate/make a new one
   

Requirements:

• Strong proficiency in SQL and a solid understanding of data modeling concepts
• Proficiency with Python, ideally data analysis/science packages like Pandas and Stats
• Good “Data storytelling” and stakeholder communication: can explain technical concepts in an intuitive way
• Detail-oriented: can sense-check your output and correct errors before sharing results with stakeholders

• A good product-sense and familiarity with fundamental “product” metrics (like DAU, retention, etc)

   

What We Offer:

• 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
• 20 working days of annual vacation leave
• English courses, Educational Events & Conferences

• Medical insurance

   

Join us at Provectus to be a part of a team that is dedicated to building cutting-edge technology solutions that have a positive impact on society. Our company specializes in AI and ML technologies, cloud services, and data engineering, and we take pride in our ability to innovate and push the boundaries of what's possible.

As an ML Engineer, you’ll be provided with all opportunities for development and growth.

Let's work together to build a better future for everyone!
 

Requirements:

• Comfortable with standard ML algorithms and underlying math.
• Strong hands-on experience with LLMs in production, RAG architecture, and agentic systems
• AWS Bedrock experience strongly preferred
• Practical experience with solving classification and regression tasks in general, feature engineering.
• Practical experience with ML models in production.
• Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines.
• Solid software engineering skills (i.e., ability to produce well-structured modules, not only notebook scripts).
• Python expertise, Docker.
• English level - strong Intermediate.
• Excellent communication and problem-solving skills.
   

Will be a plus:

• Practical experience with cloud platforms (AWS stack is preferred, e.g. Amazon SageMaker, ECR, EMR, S3, AWS Lambda).
• Practical experience with deep learning models.
• Experience with taxonomies or ontologies.
• Practical experience with machine learning pipelines to orchestrate complicated workflows.
• Practical experience with Spark/Dask, Great Expectations.
   

Responsibilities:

• Create ML models from scratch or improve existing models. 
• Collaborate with the engineering team, data scientists, and product managers on production models.
• Develop experimentation roadmap. 
• Set up a reproducible experimentation environment and maintain experimentation pipelines.
• Monitor and maintain ML models in production to ensure optimal performance.
• Write clear and comprehensive documentation for ML models, processes, and pipelines.
• Stay updated with the latest developments in ML and AI and propose innovative solutions.

Join us at Provectus to be a part of a team that is dedicated to building cutting-edge technology solutions that have a positive impact on society. Our company specializes in AI and ML technologies, cloud services, and data engineering, and we take pride in our ability to innovate and push the boundaries of what's possible.

As an ML Engineer, you’ll be provided with all opportunities for development and growth.

Let's work together to build a better future for everyone!
 

Requirements:

• Comfortable with standard ML algorithms and underlying math.
• Strong hands-on experience with LLMs in production, RAG architecture, and agentic systems
• AWS Bedrock experience strongly preferred
• Practical experience with solving classification and regression tasks in general, feature engineering.
• Practical experience with ML models in production.
• Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines.
• Solid software engineering skills (i.e., ability to produce well-structured modules, not only notebook scripts).
• Python expertise, Docker.
• English level - strong Intermediate.
• Excellent communication and problem-solving skills.
   

Will be a plus:

• Practical experience with cloud platforms (AWS stack is preferred, e.g. Amazon SageMaker, ECR, EMR, S3, AWS Lambda).
• Practical experience with deep learning models.
• Experience with taxonomies or ontologies.
• Practical experience with machine learning pipelines to orchestrate complicated workflows.
• Practical experience with Spark/Dask, Great Expectations.
   

Responsibilities:

• Create ML models from scratch or improve existing models. 
• Collaborate with the engineering team, data scientists, and product managers on production models.
• Develop experimentation roadmap. 
• Set up a reproducible experimentation environment and maintain experimentation pipelines.
• Monitor and maintain ML models in production to ensure optimal performance.
• Write clear and comprehensive documentation for ML models, processes, and pipelines.
• Stay updated with the latest developments in ML and AI and propose innovative solutions.

Join us at Provectus to be a part of a team that is dedicated to building cutting-edge technology solutions that have a positive impact on society. Our company specializes in AI and ML technologies, cloud services, and data engineering, and we take pride in our ability to innovate and push the boundaries of what's possible.

As an ML Engineer, you’ll be provided with all opportunities for development and growth.

Let's work together to build a better future for everyone!
 

Requirements:

• Comfortable with standard ML algorithms and underlying math.
• Strong hands-on experience with LLMs in production, RAG architecture, and agentic systems
• AWS Bedrock experience strongly preferred
• Practical experience with solving classification and regression tasks in general, feature engineering.
• Practical experience with ML models in production.
• Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines.
• Solid software engineering skills (i.e., ability to produce well-structured modules, not only notebook scripts).
• Python expertise, Docker.
• English level - strong Intermediate.
• Excellent communication and problem-solving skills.
   

Will be a plus:

• Practical experience with cloud platforms (AWS stack is preferred, e.g. Amazon SageMaker, ECR, EMR, S3, AWS Lambda).
• Practical experience with deep learning models.
• Experience with taxonomies or ontologies.
• Practical experience with machine learning pipelines to orchestrate complicated workflows.
• Practical experience with Spark/Dask, Great Expectations.
   

Responsibilities:

• Create ML models from scratch or improve existing models. 
• Collaborate with the engineering team, data scientists, and product managers on production models.
• Develop experimentation roadmap. 
• Set up a reproducible experimentation environment and maintain experimentation pipelines.
• Monitor and maintain ML models in production to ensure optimal performance.
• Write clear and comprehensive documentation for ML models, processes, and pipelines.
• Stay updated with the latest developments in ML and AI and propose innovative solutions.

EPAM GenAI Consultants are changemakers who bridge strategy and technology—applying agentic intelligence, RAG, and multimodal AI to transform how enterprises operate, serve users, and make decisions. 

Preferred Tech stack 

 Programming Languages 

• Python (*) 
• TypeScript 
• Rust 
• Mojo 
• Go 

 Fine-Tuning & Optimization 

• LoRA (Low-Rank Adaptation) 
• PEFT (Parameter-Efficient Fine-Tuning) 

Foundation & Open Models 

• OpenAI (GPT series), Anthropic Claude Family, Google Gemini, Grok (*, at least one of them ) 
• Llama 
• Falcon 
• Mistral 

Inference Engines  

• VLLM 

 Prompting & Reasoning Paradigms (*) 

• CoT (Chain of Thought) 
• ToT (Tree of Thought) 
• ReAct (Reasoning + Acting) 
• DSPy 

Multimodal AI Models 

• CLIP (*) 
• BLIP2 
• Whisper 
• LLaVA 
• SAM (Segment Anything Model) 

 Retrieval-Augmented Generation (RAG) 

• RAG (core concept) (*) 
• RAGAS (RAG evaluation and scoring) (*) 
• Haystack (RAG orchestration & experimentation) 
• LangChain Evaluation (LCEL Eval) 

Agentic Frameworks 

• CrewAI  (*) 
• AutoGen, AutoGPT, LangGraph, Semantic Kernel, LangChain (* at least  2 of them) 
• Prompt Tools:  PromptLayer, PromptFlow (Azure),  Guidance by Microsoft (* at least one of them) 

Evaluation & Observability 

• RAGAS – Quality metrics for RAG (faithfulness, context precision, etc.) (*) 
• TruLens – LLM eval with attribution and trace inspection (*) 
• EvalGAI – GenAI evaluation testbench 
• Giskard – Bias and robustness testing for NLP 
• Helicone – Real-time tracing and logging for LLM apps 
• HumanEval – Code generation correctness testing 
• OpenRAI – Evaluation agent orchestration 
• PromptBench – Prompt engineering comparison 
• Phoenix by Arize AI – Multimodal and LLM observability 
• Zeno – Human-in-the-loop LLM evaluation platform 
• LangSmith – LangChain observability and evaluation 
• WhyLabs – Data drift and model behavior monitoring 

Explainability & Interpretability (understanding) 

• SHAP 
• LIME 

Orchestration & Experimentation (*) 

• MLflow 
• Airflow 
• Weights & Biases (W&B) 
• LangSmith 

 Infrastructure & Deployment 

• Kubernetes 
• Amazon SageMaker 
• Microsoft Azure AI 
• Goggle Vertex AI  
• Docker 
• Ray Serve (for distributed model serving) 

Responsibilities 

• Lead GenAI discovery workshops with clients
• Design Retrieval-Augmented Generation (RAG) systems and agentic workflows
• Deliver PoCs and MVPs using LangChain, LangGraph, CrewAI , Semantic Kernel,  DSPy, RAGAS 
• Ensure Responsible AI principles in deployments (bias, fairness, explainability) 
• Support RFPs, technical demos, and GenAI architecture narratives 
• Reuse of accelerators/templates for faster delivery 
• Governance & compliance setup for enterprise-scale AI 
• Use of evaluation frameworks to close feedback loops 

Requirements 

• Consulting: Experience in exploring the business problem and converting it to applied AI technical solutions; expertise in pre-sales, solution definition activities 
• Data Science: 3+ years of hands-on experience with core Data Science, as well as knowledge of one of the advanced Data Science and AI domains (Computer Vision, NLP, Advanced Analytics etc.)   
• Engineering: Experience delivering applied AI from concept to production, familiarity, and experience with MLOps, Data, design of Data Analytics platforms, data engineering, and technical leadership 
• Leadership: Track record of delivering complex AI-empowered and/or AI-empowering programs to clients in a leadership position. Experience in managing and growing a team to scale up Data Science, AI, and ML capabilities is a big plus. 
• Excellent communication skills (active listening, writing and presentation), drive for problem solving and creative solutions, high EQ 
• Experience with LLMOps or GenAIOps tooling (e.g., guardrails, tracing, prompt tuning workflows) 
• Understanding of the importance of AI products evaluation is a must 
• Knowledge of cloud GenAI platforms (AWS Bedrock, Azure OpenAI, GCP Vertex AI) 
• Understanding of data privacy, compliance, and Governance in GenAI (GDPR, HIPAA, SOC2, RAI, etc.) 
• In-depth understanding of a specific industry or a broad range of industries.