Jobs

We are looking for a Data Scientist  (4 months project) 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)
• Interview with Global Head of Data(30 min)
• HR Interview (30 min)
• Reference Checks

We offer:

• Competitive compensation based on your skills and experience
• Exciting projects involving the newest technologies

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.

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 looking for an AI Datasets Lead (data generation & annotation) to join our AI team to oversee the entire data annotation process, supporting our AI and machine learning initiatives. 

This role requires strong leadership skills combined with a good understanding of data collection and annotation for machine learning models.
In this role, you will be central to ensuring the efficiency, accuracy, and success of our data labeling processes.

If it sounds interesting to you, then look no further — send us your CV!

In this role, you will:

• Organize and supervise the data annotation process, ensuring its accuracy and quality
• Build and lead the data annotation team, coordinate team tasks and workflows, and foster the team development
• Implement quality control processes, analyze errors, and improve standards
• Develop and maintain annotation guidelines and documentation to ensure consistency and accuracy across the team
• Optimize annotation processes and explore automation opportunities
• Closely collaborate with data engineers to develop efficient data processing solutions and tools, and implement automated data processing workflows to streamline annotation processes
• Collaborate closely with ML Engineers to align data annotation efforts with machine learning model requirements and understand the neural network training process
• Take part in cross-functional coordination and cooperation with other colleagues
• Manage costs related to data sourcing and annotation
• Explore outsourcing & alternative data solutions, manage cooperation with external freelancers and partners, including searching, selecting, and organizing cooperation with them to meet the organizational needs
• Ensure compliance with data privacy and security regulations throughout the data annotation process

Skills you’ll need to bring:

• Proven experience leading a data annotation team
• Basic understanding of AI/ML concepts (data annotation needs, task types, neural network training)
• Good knowledge of data labeling processes and familiarity with relevant tools, platforms, and best practices in the data annotation field
• Basic understanding of data collection processes (web scraping, dataset management)
• Strong leadership, communication, and organizational skills with the ability to convey technical aspects to both technical and non-technical stakeholders
• Strong ability to manage uncertainty and bring clarity to unstructured situations — handle incoming requests without predefined processes, structure the chaos, and progressively build clear, actionable workflows for the team
• Experience with quality assurance processes for large datasets
• Keen attention to detail and the ability to balance multiple projects and priorities simultaneously
• Openness to frequent feedback from multiple stakeholders and readiness to quickly adapt processes in real time based on that input
• Experience with data privacy regulations and ethical considerations in data annotation
• Strong analytical skills to monitor processes and implement improvements based on data-driven insights
• Ability to develop and implement data quality metrics and KPIs to measure the effectiveness of annotation processes
• Experience managing budgets & external partnerships
• Intermediate level of English or higher

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.
• 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.

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!

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.

Overview

We are seeking a highly skilled and experienced Senior/Lead Computer Vision Engineer specializing in Navigation to join our innovative R&D team. In this pivotal role, you will drive the development and deployment of state-of-the-art computer vision algorithms for autonomous navigation systems, contributing to our efforts in robotics, autonomous vehicles, drones, or similar fields. You will work cross-functionally with engineering, product, and research teams to deliver robust, real-time solutions that enable safe and intelligent navigation in dynamic environments.

Responsibilities

• Lead the design, development, and optimization of computer vision algorithms for localization, mapping, and navigation.
• Develop and implement algorithms for object detection, segmentation, SLAM, 3D scene reconstruction, visual odometry, and sensor fusion (using cameras, LiDAR, IMUs, etc.).
• Guide the integration of computer vision modules with navigation and control systems, ensuring seamless operation in real-world conditions.
• Collaborate with software, hardware, and product teams to define requirements and deliver scalable, robust navigation solutions.
• Stay current with advancements in deep learning, computer vision, and robotics, and introduce relevant state-of-the-art techniques into the product.
• Design and execute experiments to evaluate performance and robustness; analyze results and iterate on solutions.
• Prepare technical documentation, progress reports, and presentations for internal and external stakeholders.

Requirements

• 5+ years of experience in computer vision, preferably in navigation, robotics, or autonomous systems.
• Master’s or PhD in Computer Science, Robotics, Electrical Engineering, or related field.
• Strong proficiency in Python and/or C++.
• Hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and classical computer vision libraries (e.g., OpenCV, PCL).
• Experience in deploying and optimizing models for single-board computers such as Raspberry Pi, Nvidia Jetson
• Proven track record of developing and deploying real-time vision algorithms for navigation tasks in challenging environments.
• Extensive knowledge of SLAM, visual odometry, sensor fusion, and related algorithms.
• Experience with ROS, embedded systems, and real-time software development is a plus.
• Excellent problem-solving skills, strong analytical mindset, and effective communication abilities.

Preferred Qualifications

• Knowledge of SLAM and related models.
• Familiarity with the MAVLink protocol and ArduPilot.
• Familiarity with edge computing or real-time GPU-based inference.
• Publications or contributions to the open-source community in vision or robotics.

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. 

About Us

Cherry is a fast-growing market place for buying, selling, leasing, and auctioning commercial vehicles and equipment. We’re building an industry-first valuation engine that helps our users make informed decisions in seconds. Now, we’re looking for a Machine Learning Engineer who can bring strong expertise in predictive modeling, and ideally document automation using AI.

Role Overview

We are seeking an experienced ML specialist to build models that predict market prices for trucks and equipment based on auction results, historical sales, and vehicle specifications. This role will also involve setting up automated data pipelines, scraping structured and semi-structured data, and optionally working on generating intelligent reports or documents from data.

Key Responsibilities

• Build and refine price prediction models using data from auction sites, dealership listings, and historical records.
• Design and maintain data scraping pipelines will be a plus (e.g., BeautifulSoup, Selenium, Scrapy) to gather auction and sale data from multiple public sources.
• Clean, normalize, and store data efficiently for training and inference.
• Apply feature engineering techniques on specs like make, model, mileage, year, VIN, etc.
• Work closely with product and engineering teams to deploy models in production.
• (Optional but valued): Use NLP or generative AI to create documents or listing descriptions automatically.

Requirements

• Proven experience in machine learning with a focus on regression/predictive models.
• Strong Python skills; familiar with tools like Scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch.
• Experience in web scraping is a plus (BeautifulSoup, Scrapy, etc.).
• Familiarity with model evaluation metrics for regression (e.g., RMSE, MAE).
• Comfortable working with structured data (CSV, JSON, APIs) and preprocessing pipelines.
• Fluent in Git and version control workflows.
• Experience deploying or working with models in production (FastAPI, Flask, AWS/GCP preferred).

Nice to Have

• Familiarity with automated document generation, AI agents, or LLM APIs (OpenAI, Langchain).

   

We are looking for a Computer Vision Engineer with a background in classical computer vision techniques and hands-on implementation of low-level CV algorithms.

The ideal candidate will have experience with SLAM, Visual-Inertial Odometry (VIO), and sensor fusion.

We consider engineers at Middle/Senior levels — tasks and responsibilities will be adjusted accordingly.

Required Qualifications:

• 3+ years of hands-on experience with classical computer vision
• Knowledge of popular computer vision networks and components 
• Understanding of geometrical computer vision principles
• Hands-on experience in implementing low-level CV algorithms
• Practical experience with SLAM and/or Visual-Inertial Odometry (VIO)
• Proficiency in C++
• Experience with Linux
• Ability to quickly navigate through recent research and trends in computer vision.

Nice to Have:

• Experience with Python
• Familiarity with neural networks and common CV frameworks/libraries (OpenCV, NumPy, PyTorch, ONNX, Eigen, etc.)
• Experience with sensor fusion.

FAVBET Tech develops software that is used by millions of players around the world for the international company FAVBET Entertainment.
We develop innovations in the field of gambling and betting through a complex multi-component platform which is capable to withstand enormous loads and provide a unique experience for players.
 

FAVBET Tech does not organize and conduct gambling on its platform. Its main focus is software development.

Main areas of work:

• Betting/Gambling Platform Software Development — software development that is easy to use and personalized for each customer.
• Highload Development — development of highly loaded services and systems.
• CRM System Development — development of a number of services to ensure a high level of customer service, effective engagement of new customers and retention of existing ones.
• Big Data — development of complex systems for processing and analysis of big data.
• Cloud Services — we use cloud technologies for scaling and business efficiency.

Responsibilities:

• Developing and design the math side of casino games, mostly slot machines
• Determine and calculate the probabilities, build game behavior and properties
• Cooperate with product managers and developers
• Come up with new and innovative ideas and also be aware of existing features in the industry
• Maintenance of existing games
• Work closely with development teams

Requirements:

• BS/MS degree in Mathematics, statistics or similar disciplines with a very strong mathematical skill
• Experience in gaming industry 2+ years
• Extremely details oriented, fast learning and highly motivated person
• Creative, productive, working as part of a team, responsible
• Basic programming knowledge
• Advanced programming — advantage
• Strong communication skills

We offer:

• 30 day off — we value rest and recreation;
• Medical insurance for employees and the possibility of training employees at the expense of the company and gym membership;
• Remote work or the opportunity — our own modern lofty office with spacious workplace, and brand-new work equipment (near Pochaina metro station);
• Flexible work schedule — we expect a full-time commitment but do not track your working hours;
• Flat hierarchy without micromanagement — our doors are open, and all teammates are approachable.

During the war, the company actively supports the Ministry of Digital Transformation of Ukraine in the initiative to deploy an IT army and has already organized its own cyber warfare unit, which makes a crushing blow to the enemy’s IT infrastructure 24/7, coordinates with other cyber volunteers and plans offensive actions on its IT front line.

Technologies

• Python, Databricks, Azure ML, Big Data (Hadoop, Spark, Hive, etc.), AWS, Docker, Kubernetes, DB (Pl SQL, HQL, Mongo), Google (Vertex AI) or similar

Responsibilities

• Discover, envision and land Data Science, AI and Machine Learning opportunities alongside EPAM teams & clients
• Lead cross-functional EPAM and/or EPAM clients` teams through the journey of understanding business challenges and defining solutions leveraging AI, Data Science, Machine Learning and MLOps 
• Work with clients to deliver AI Products which provide value to end-users 
• Participate and drive EPAM competencies development, work on new EPAM offerings in AI, Data Science, ML and MLE space, as well as work on refining existing offerings 
• Bring your creative engineering mind to deliver real-life practical applications of Machine Learning 
• Work closely with DevOps practice on infrastructure and release planning 

Requirements

• Consulting: Experience in exploring the business problem and converging 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 the clients in a leadership position. Experience managing and growing the team to scale up Data Science, AI &ML capability is a big plus
• Excellent communication skills (active listening, writing and presentation), drive for problem solving and creative solutions, high EQ

Nice to have

• One or more business domains expertise (e.g. CPG, Retail, Financial Services, Insurance, Healthcare/ Life Science)

We offer

• Work on a flexible schedule remotely or from any of our comfortable offices or coworking spaces in Ukraine
• Receive the necessary equipment to perform your work tasks
• Change projects and technology stacks within EPAM
• Gain experience in various business domains (Insurance, E-commerce, Healthcare, Finance, Travelling, Media, Artificial Intelligence, and more)
• Consider relocation options in over 30 countries worldwide
• Participate in volunteer, charity programs and communities (both technical and interest-based)
• You can plan your individual career path together with your manager
• Receive regular feedback from colleagues
• Improve your English for free with certified teachers (Speaking Clubs, client interview preparation courses, etc.)
• Get the opportunity to undergo free training and certification in AWS, GCP, or Azure Clouds
• Use the internal E-learn training program (18,200+ specialized training and mentoring programs)
• Access corporate accounts on LinkedIn Learning, Get Abstract and other partner resources
• Study at EPAM Solution Architecture School with the instructors who are practicing architects
• Develop as a leader, join Delivery Management, Resource Management, Leadership Essentials school and more
• Participate in internal communities (500+ meetups, technical discussions, brainstorming sessions, online events and conferences annually)
• Vacation and sick leave (including a sick leave without a medical certificate)
• A wide range of Voluntary Medical Insurance programs providing both medical treatment and various preventive options (including sports activities)
• Medical insurance for family members at corporate rates
• Company support during significant life events (childbirth or adoption, marriage, etc.)
• Support for psychological comfort: discounts on services from mental health specialists or coaches, thematic training
• E-kids program - a free programming language training program for EPAMers' children