Jobs

DataRoot Labs is a full-cycle AI R&D center—and Ukraine’s largest hub of AI talent and compute. Over the past 10+ years, we’ve shipped 45+ AI-powered products for leaders and startups across Automotive, Energy, Navigation, Gaming, Education, and more
 

Our client builds autonomous yard trucks that replace human drivers to make logistics yards safer, faster, and more efficient
 

Your mission: make the AI stack see in 3D and drive correctly—every time

Responsibilities:

• Invent & build computer vision algorithms with a focus on 3D object detection and scene reconstruction
• Own productionization: collaborate with ML/Robotics/Platform teams to ship robust, low-latency vision models

• Push the frontier: work hands-on with modern 3D vision, Deep Learning, and RL/VLA-aware pipelines

   

Requirements:

• Strong background in Computer Vision and Deep Learning
• Hands-on experience with RGB-based 3D detection and occupancy networks
• Proficiency with PyTorch or TensorFlow
• Experience in 3D reconstruction, point clouds, or related domains
• Python mastery; solid problem-solving and analytical skills
• Upper-Intermediate English (written & spoken)
• Experience with inference optimization (e.g., quantization/acceleration) is a plus

Would be a plus:

• Knowledge or practical experience with Reinforcement Learning
• Work with edge devices & sensors (cameras, LiDAR, radar, etc.)
• Background in automotive or robotics
• C++/CUDA familiarity

What We Offer:

• Real autonomy impact. Work on vehicles that use RL, Vision-Language-Action (VLA) and many other latest architectures
• Access to DGX H200 systems and large-scale GPU clusters
• Startup pace, research mindset, and a goal-oriented team
• Newest technical equipment and modern MLOps
• 20 working days of paid vacation, English courses, educational events & conferences, and medical insurance
• Your engineering will directly influence how autonomous vehicles perceive and act

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 experienced Senior Data Scientist / NLP Lead to spearhead the development of cutting-edge natural language processing solutions for the Ukrainian LLM project. You will lead the NLP team in designing, implementing, and deploying large-scale language models and NLP algorithms that power the products.

This role is critical to the mission of advancing AI in the Ukrainian language context, and offers the opportunity to drive technical decisions, mentor a team of data scientists, and shape the future of AI capabilities in Ukraine.
 

Requirements:
Education & Experience:
- 5+ years of experience in data science or machine learning, with a strong focus on NLP.
- Proven track record of developing and deploying NLP or ML models at scale in production environments.
- An advanced degree (Master’s or PhD) in Computer Science, Computational Linguistics, Machine Learning, or a related field is highly preferred.

NLP Expertise:
- Deep understanding of natural language processing techniques and algorithms.
- Hands-on experience with modern NLP approaches, including embedding models, text classification, sequence tagging (NER), and transformers/LLMs.
- Deep understanding of transformer architectures and knowledge of LLM training and fine-tuning techniques, hands-on experience developing solutions on LLM, and knowledge of linguistic nuances in Ukrainian or other languages.

Advanced NLP/ML Techniques:
- Experience with evaluation metrics for language models (perplexity, BLEU, ROUGE, etc.) and with techniques for model optimization (quantization, knowledge distillation) to improve efficiency.
- Background in information retrieval or RAG (Retrieval-Augmented Generation) is a plus for building systems that augment LLMs with external knowledge.
ML & Programming Skills:
- Proficiency in Python and common data science libraries (pandas, NumPy, scikit-learn).
- Strong experience with deep learning frameworks such as PyTorch or TensorFlow for building NLP models.
- Ability to write efficient, clean code and debug complex model issues.

Data & Analytics:
- Solid understanding of data analytics and statistics.
- Experience in experimental design, A/B testing, and statistical hypothesis testing to evaluate model performance.
- Experience on how to build a representative benchmarking framework given business requirements for LLM.
- Comfortable working with large datasets, writing complex SQL queries, and using data visualization to inform decisions.

Deployment & Tools:
- Experience deploying machine learning models in production (e.g., using REST APIs or batch pipelines) and integrating with real-world applications.
- Familiarity with MLOps concepts and tools (version control for models/data, CI/CD for ML).
- Experience with cloud platforms (AWS, GCP or Azure) and big data technologies (Spark, Hadoop) for scaling data processing or model training is a plus.
- Hands-on experience with containerization (Docker) and orchestration (Kubernetes) for ML, as well as ML workflow tools (MLflow, Airflow).
Leadership & Communication:
- Demonstrated ability to lead technical projects and mentor junior team members.
- Strong communication skills to convey complex ML results to non-technical stakeholders and to document methodologies clearly.

Responsibilities:
- Lead end-to-end development of NLP and LLM models - from data exploration and model prototyping to validation and production deployment. This includes designing novel model architectures or fine-tuning state-of-the-art transformer models (e.g., BERT, GPT) to solve project-specific language tasks.
- Analyze large text datasets (Ukrainian and multilingual corpora) to extract insights and build robust training datasets.
- Guide data collection and annotation efforts to ensure high-quality data for model training.
- Develop and implement NLP algorithms for a range of tasks such as text classification, named entity recognition, semantic search, and conversational AI.
- Stay up-to-date with the latest research to apply transformer-based models, embeddings, and other modern NLP techniques in the solutions.
- Establish evaluation metrics and validation frameworks for model performance, including accuracy, factuality, and bias.
- Design A/B tests and statistical experiments to compare model variants and validate improvements.
- Deploy and integrate NLP models into production systems in collaboration with engineers - ensuring models are scalable, efficient, and well-monitored in a real-world setting.
- Optimize model inference and troubleshoot issues such as model drift or data pipeline bottlenecks.
- Provide technical leadership and mentorship to the NLP/ML team.
- Review code and research, uphold best practices in ML (version control, reproducibility, documentation), and foster a culture of continuous learning and innovation.
- Collaborate cross-functionally with product managers, software engineers, and MLOps engineers to align NLP solutions with product goals and infrastructure capabilities.
- Communicate complex data science concepts to stakeholders and incorporate their feedback into model development.

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.

DataRoot Labs is a full-cycle AI R&D center—and Ukraine’s largest hub of AI talent and compute. Over the past 10+ years, we’ve shipped 45+ AI-powered products for leaders and startups across Automotive, Energy, Navigation, Gaming, Education, and more
 

Our client builds autonomous yard trucks that replace human drivers to make logistics yards safer, faster, and more efficient
 

Your mission: make the AI stack see in 3D and drive correctly—every time

Responsibilities:

• Research and develop advanced reinforcement learning (RL) algorithms and their applications
• Build, simulate, and test RL environments for real-world deployment scenarios
• Apply modern deep learning techniques, including transformers and computer vision, to RL problems
• Optimize inference performance for large-scale RL solutions

Requirements:

• Have a strong background in Reinforcement Learning and Deep Learning
• Hands-on experience with simulation and environments for RL
• Proven production experience in RL, including deployment cases
• Deep understanding of RL techniques (e.g., policy gradients, actor-critic, Q-learning)
• Experience with transformers and computer vision
• Upper-Intermediate English (written & spoken) for documentation and collaboration
• Strong knowledge of Python
• Experience with inference optimization

Would be a plus:

• Experience with Vision-Language Architectures (VLAs)
• Work with edge devices and sensors (e.g., camera, lidar, radar, etc.)
• Experience in automotive or robotics
• Knowledge of C++/CUDA

What We Offer:

• Real autonomy impact. Work on vehicles that use RL, Vision-Language-Action (VLA) and many other latest architectures
• Access to DGX H200 systems and large-scale GPU clusters
• Startup pace, research mindset, and a goal-oriented team
• Newest technical equipment and modern MLOps
• 20 working days of paid vacation, English courses, educational events & conferences, and medical insurance
• Your engineering will directly influence how autonomous vehicles perceive and act

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, FinOps, and GenAI solutions that drive 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’re looking for a hands-on Data Science Team Lead to build and scale production AI/ML solutions on AWS while leading a Data Scientist team. You’ll own the full lifecycle —from discovery and proof-of-concepts to training, optimization, deployment, and iteration in production — partnering closely with customers and cross-functional teams.

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

Responsibilities

• People leadership: Manage and coach a team of Data Scientists, set clear goals, run 1:1s, and support career growth and technical excellence.
• Delivery ownership: Drive project scoping, planning, and on-time, high-quality delivery from inception to production. Proactively remove blockers, manage risks, and communicate status to stakeholders.
• Customer engagement: Work directly with founders/technical leaders to understand goals, translate them into feasible AI roadmaps, and ensure measurable business outcomes.
• Model Development & Deployment: Deploy and train models on AWS SageMaker (using TensorFlow/PyTorch).
• Model Tuning & Optimization: Fine-tune and optimize models using techniques like quantization and distillation, and tools like Pruna.ai and Replicate.
• Generative AI Solutions: Design and implement advanced GenAI solutions, including prompt engineering and retrieval-augmented generation (RAG) strategies.
• LLM Workflows: Develop agentic LLM workflows that incorporate tool usage, memory, and reasoning for complex problem-solving.
• Scalability & Performance: Maximize model performance on AWS’s by leveraging techniques such as model compilation, distillation, and quantization and using AWS specific features.

• Collaboration: Work closely with other teams (Data Engineering, DevOps, MLOps, Solution Architects, Sales teams) to integrate models into production pipelines and workflows.

   

Requirements

• Team management experience: 2+ years leading engineers or scientists (people or tech lead).
• Technical experience: 5–6+ years in Data Science/ML (including deep learning/LLMs).
• Excellent customer-facing skills to understand and address client needs effectively.
• Expert in Python and deep learning frameworks (PyTorch/TensorFlow), and hands-on with AWS ML services (especially SageMaker and Bedrock).
• Proven experience with generative AI and fine-tuning large language models.
• Experience deploying ML solutions on AWS cloud infrastructure and familiarity with MLOps best practices.
• Fluent written and verbal communication skills in English.

• A master’s degree in a relevant field and AWS ML certifications are a plus.

   

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, recognizing the value you bring to our team.

Junior Data Scientist / Data Engineer | Blockchain | On-Chain Analytics
Location: Remote
Type: Full-time
 

Everstake is the largest blockchain network validator in Ukraine and one of the top players in global Web3 infrastructure. We support dozens of networks worldwide and are scaling fast.

We are looking for an exceptional Data Scientist / Data Engineer to join our team. The ideal candidate has a strong passion for blockchain technology and a proven track record of leveraging data to drive insights and business decisions.

About the Role

You’ll be responsible for conducting deep analysis of on-chain data, developing hypotheses to improve profitability, and creating tools to automate data collection and analysis. Your work will have a direct impact on strategy and decision-making at Everstake.

What You’ll Do

• Conduct deep analysis of on-chain data to identify trends, patterns, and insights.
• Propose and test hypotheses that can increase company revenue and efficiency.
• Collaborate with cross-functional teams to translate data into actionable recommendations.
• Build and maintain tools and scripts for data collection, processing, and analysis.
• Create reports, dashboards, and visualizations (e.g., PowerBI, Tableau) using blockchain data.
• Communicate findings clearly to both technical and non-technical stakeholders.
• Stay up-to-date with blockchain innovations and apply them to on-chain analytics.
   

What We’re Looking For

• Bachelor’s or Student degree in Computer Science, Data Science, or a related field.
• Proficiency with SQL or SQL-like query languages.
• Experience working with large datasets and data analysis libraries (e.g., Pandas, NumPy, SciPy).
• Strong background in blockchain technology and on-chain data analysis.
• Hands-on experience with data visualization tools (PowerBI, Tableau, or similar).
• Excellent analytical, problem-solving, and critical-thinking skills.
• Strong written and verbal communication skills.
   

Nice to Have

• Experience with big data frameworks (e.g., Spark, Hadoop).
• Familiarity with Web3 analytics platforms and APIs.
• Contributions to blockchain / crypto open-source projects.
• Knowledge of statistical modeling or machine learning methods.

We are seeking a highly skilled Machine Learning Engineer with expertise in Deep Learning, Natural Language Processing (NLP), and Large Language Models (LLMs). You will be responsible for designing, building, and deploying advanced ML models and pipelines, ensuring scalability, performance, and production readiness. The ideal candidate has strong research knowledge combined with hands-on engineering skills to deliver intelligent, enterprise-grade AI solutions.

Details:
Location: Remote in EU
Employment Type: Full-Time, B2B Contract
Start Date: ASAP
Language Requirements: Fluent English

Key Responsibilities

• Design, develop, and optimize ML models with a focus on deep learning, NLP, and LLM-based applications.
• Build scalable pipelines for training, fine-tuning, evaluation, and deployment of models.
• Work with frameworks such as PyTorch, TensorFlow, and Hugging Face Transformers.
• Fine-tune and adapt pre-trained LLMs (GPT, BERT, LLaMA, etc.) for domain-specific tasks.
• Develop solutions for text classification, summarization, embeddings, RAG, and conversational AI.
• Ensure model scalability, robustness, and low-latency performance in production environments.
• Collaborate with data engineers to prepare and optimize large-scale datasets.
• Implement MLOps practices (CI/CD, monitoring, retraining, governance).
• Participate in code reviews, documentation, and technical knowledge sharing.

Requirements

• 5+ years of experience in machine learning, with at least 3+ years focused on deep learning/NLP.
• Strong expertise in PyTorch or TensorFlow, and NLP frameworks (Hugging Face, spaCy, NLTK).
• Hands-on experience with LLMs (GPT, T5, LLaMA, Falcon, etc.), fine-tuning and prompt engineering.
• Proficiency in Python and libraries (NumPy, Pandas, Scikit-learn).
• Experience with MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML).
• Strong understanding of transformer architectures, embeddings, and attention mechanisms.
• Familiarity with cloud platforms (AWS, Azure, GCP) for ML deployment.
• Excellent problem-solving and debugging skills.

Nice to Have

• Experience with vector databases (Pinecone, Weaviate, Milvus) for semantic search.
• Knowledge of retrieval-augmented generation (RAG) pipelines.
• Exposure to multimodal ML (text + image/audio/video).
• Contributions to open-source ML/NLP projects.
• Advanced degree (MSc/PhD) in Computer Science, AI, or related field.
• Industry background in fintech, healthcare, telecom, or e-commerce.

About the Role

We’re seeking a Team Lead – Generative AI Engineer to lead a team of engineers in designing, developing, and deploying production-grade AI systems. This role is ideal for someone who is both a strong technical contributor and an experienced people leader—capable of driving architecture decisions, mentoring team members, and delivering innovative AI solutions at scale.

You will be responsible for guiding the end-to-end lifecycle of Generative AI applications, ensuring technical excellence, scalability, and alignment with business needs. This includes working across backend systems, RAG pipelines, prompt engineering, and cloud-native deployments.

Key Responsibilities

• Leadership & Team Management
  • Lead and mentor a team of AI/ML engineers, fostering growth and technical excellence.
  • Define and enforce coding standards, architectural patterns, and best practices.
  • Collaborate with stakeholders to translate business needs into AI-driven solutions.
  • Manage project timelines, technical risks, and team deliverables.
  • Generative AI & Prompt Engineering
    • Integrate and optimize applications using LLM provider APIs (OpenAI, Anthropic, etc.).
    • Design prompts with advanced techniques (few-shot, chain-of-thought, chaining, context crafting).
    • Implement safeguards (guardrails, structured output validation, injection protection).
  • Architecture & Backend Development
    • Build scalable backend services in .NET (C#) and Python, working with SQL and APIs.
    • Develop and manage RAG pipelines, conversational AI systems, and summarization tools.
    • Drive observability: tracing, logging, monitoring for LLM-powered systems.

  • Evaluation & Optimization

    • Benchmark and evaluate LLMs using custom datasets and automated testing.
    • Oversee system reliability, performance tuning, caching, and optimization.
    • Ensure solutions meet enterprise-grade standards for security and scalability.

     

    Required Skills & Qualifications

  • 5+ years of professional experience in Machine Learning / AI engineering.
  • 1–2+ years hands-on experience in Generative AI application development.
  • Proven leadership or team lead experience (mentoring, managing, or leading AI/ML engineers).
  • Strong backend engineering skills in .NET (C#), SQL, and Python.
  • Solid knowledge of LLM providers (OpenAI, Anthropic, etc.) and prompt engineering techniques.
  • Experience with RAG pipelines, AI workflows, and productionizing LLM systems.
  • Hands-on with Docker, Kubernetes, REST APIs, and Azure (AKS, ACR, containerized deployments).
  • Excellent communication skills (English, written and spoken).
  • Preferred / Nice-to-Have
  • Azure AI ecosystem: OpenAI, PromptFlow, Azure ML, AI Services.
  • Familiarity with CosmosDB, KQL, Azure Log Analytics, App Insights.
  • Experience with multiple LLM providers (Anthropic, Mistral, Cohere, etc.)
  • Prompt caching, compression, and output validation strategies.
  • Redis caching for performance optimization.
  • Frontend experience with React and Next.js.

We’re looking for a proactive Data Scientist to join our growing team and help us redefine the future of eSports betting! You will develop and implement advanced models for esports betting, focusing on games such as Dota 2, League of Legends, etc. Oversee the entire model development lifecycle, including design, testing, and performance optimization.

What you’ll be doing:

• Develop and implement betting models using Python and Golang.
• Design and optimize mathematical models, including statistical models, classical machine learning techniques, and neural networks.
• Analyze the performance and impact of models, ensuring operational efficiency.
• Prototype and assess models to evaluate their effectiveness and user acceptance.
• Integrate models with existing systems and optimize performance.
• Collaborate with backend and frontend teams for seamless implementation and decision-making.
• Conduct in-depth statistical analysis and apply machine learning methods to enhance forecasting accuracy.

What we’re looking for:

• 3+ years of commercial experience with Python.
• Strong knowledge of statistics and practical experience with ML techniques.
• Proven expertise in mathematical modeling, including statistical methods, classical ML approaches, and neural networks.
• Strong data processing skills (validation, parsing, visualization).
• Understanding business logic of decisions and analytical thinking ability.
• Excellent communication skills and the ability to work in a team.
• Ability to assess the business value of tasks.
• English – Intermediate level.
• Nice to have: Higher education in computer science, mathematics, statistics, or a related discipline is a plus.

• Nice to have: Experience in the betting industry or related fields is an advantage.

   

What We Offer:

• Your wellbeing and a comfortable work environment are our top priorities:
• Flexible schedule & work format (office/hybrid): work where and when you feel most productive.
• 20 paid + 15 unpaid vacation days: take time off whenever you need to reset.
• An extra day off on your birthday — celebrate it your way!
• Medical insurance: take care of your health with extended coverage (available in Ukraine only).
• 22 sick days: 8 days without a doctor’s note (for sick leave or mental health), 10 with a note, plus 4 Personal Days per year — for personal matters, when it is necessary.
• Gifts and bonuses for life’s big moments: weddings, new babies, kindergarten support (available in Ukraine only).

Who We Are:

We’re DATA.BET — a product-driven IT company transforming the world of sports, esports, and virtual betting with our innovative sportsbook solution. 

Since 2017, we’ve been building tech that directly shapes the industry.
Our team of experts blends hands-on experience with AI technologies to deliver cutting-edge solutions that set new standards in betting.

Remote – Full-time – Flexible Hours - Shifted schedule to EST (New York) timezone

About TenViz

TenViz Predictive Analytics builds AI-powered solutions that help Fortune 100 investors anticipate market shifts before they become consensus. We combine financial expertise, mathematical rigor, and AI research to deliver predictive analytics for institutional investors.

Your Expertise

• Strong interest in quantitative and algorithmic approaches
• BSc/MSc in Math, Physics or related field with solid background in statistics, linear algebra and probability theory
• 2+ years in data research, quantitative modeling, ML prototyping, and backtesting
• Skilled in Python, SQL, Git
• Experience with  experiment tracking, pipeline orchestration and workflow automation

Nice to have:

• Bayesian inference, reinforcement learning, or ensemble methods
• Financial econometrics, time-series forecasting, or regime modeling

What You’ll Do

• Design predictive models using probabilistic, ML, and hybrid approaches
• Analyze large-scale financial datasets to detect hidden patterns and early regime shifts
• Prototype and evaluate algorithms, from deep learning to Bayesian models
• Write production-grade research code in Python/SQL that integrates into pipelines
• Translate results into insights and themes investors can act on — not just outputs

Example projects:

• Forecasting inflation via commodity price signals
• Constructing probabilistic forecasts of currency moves around macroeconomic announcements
• Designing a Bayesian model to estimate recession probabilities from yield curve dynamics
• Designing a regime-aware ML pipeline that switches models depending on market conditions
• Creating hybrid ensembles that outperform traditional benchmarks

What’s in It for You

• Remote-first, flexible hours
• Paid vacation & holidays (after 8 months)
• Continuous learning: advanced ML/DL workshops, probabilistic methods, optimization
• Supportive, collaborative team — no micromanagement, focus on trust and creativity
• Work on real financial problems where your models influence billion-dollar decisions

Welcome to King Group - a place where the best people from the IT and gambling industries meet to do amazing things together. We operate numerous projects in the iGaming sector in the markets of Ukraine, Europe and the USA, invest in venture startups, promising ideas and people.
 

One of our companies is a game studio that deals with the full cycle of iGaming product development. From idea to release, we combine creativity, modern technologies and deep analytics to create a unique gaming experience. Our mission is to excite, inspire and shape the future of the industry.

Our company is looking for a math expert who has a drive and passion (perhaps some experience) for games.

Key skills (it's not necessary to have all key skills, but more is better than less):

• Higher education in mathematics or related fields (related to research, analytics or data processing);
• Have a strong math background (especially probability theory, statistics, combinatorics);
• Advanced knowledge of MS Excel (statistical, mathematical functions);
• Be proficient at one (at least) programming language (Python is preferable);
• Knowledge of one of the CAS (Mathematica, Mathcad, Maxima);
• Have a strong math background (especially probability theory, statistics, combinatorics);
• Have previous experience in gaming industry or (and) have experience in playing slots (or any other probabilistic games (poker, blackjack, etc));
• Understand the time and memory complexity of your code;
• Be keen on details (Yes, it's really important at this position);
• Understanding OOP Concepts;
• Experience in developing mathematical models.
   

Nice to have:

• Experience in using git;
• Experience in using JIRA.
   

Responsibilities: 

• Prepare math for slot games;
• Discuss with business/ propose new game ideas/new feature ides;
• Implement game logic of new features, games;
• Gather games' statistics by precise calculations / running simulations of the games;
• Make games attractive for players from the math side.
   

Why we:

• Social Package;
• Medical care;
• Sick Days;
• Professional development support;
• Family-like atmosphere. You can check it out yourself ;)
• Great career prospects.
  
  Do you want to grow with us? Do you have the desire to take an active part in creating a product? Send your resume and let's get to know each other ;)

A product company is looking for an AI Lead Engineer (on-site) in Warsaw.

✅ It's a Silicon Valley Company, a successful market leader.

The B2C platform, based on the best-quality global video technology.

✅They offer: stock options grant, medical insurance (for you + 75% coverage for your relatives), free lunches and parking, multisport card.

✅Requirements: experience with Python, LLM, and RAG. Strong leadership experience.

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 experienced Senior Data Scientist / NLP Lead to spearhead the development of cutting-edge natural language processing solutions for the Ukrainian LLM project. You will lead the NLP team in designing, implementing, and deploying large-scale language models and NLP algorithms that power the products.

This role is critical to the mission of advancing AI in the Ukrainian language context, and offers the opportunity to drive technical decisions, mentor a team of data scientists, and shape the future of AI capabilities in Ukraine.
 

Requirements:
Education & Experience:
- 5+ years of experience in data science or machine learning, with a strong focus on NLP.
- Proven track record of developing and deploying NLP or ML models at scale in production environments.
- An advanced degree (Master’s or PhD) in Computer Science, Computational Linguistics, Machine Learning, or a related field is highly preferred.

NLP Expertise:
- Deep understanding of natural language processing techniques and algorithms.
- Hands-on experience with modern NLP approaches, including embedding models, text classification, sequence tagging (NER), and transformers/LLMs.
- Deep understanding of transformer architectures and knowledge of LLM training and fine-tuning techniques, hands-on experience developing solutions on LLM, and knowledge of linguistic nuances in Ukrainian or other languages.

Advanced NLP/ML Techniques:
- Experience with evaluation metrics for language models (perplexity, BLEU, ROUGE, etc.) and with techniques for model optimization (quantization, knowledge distillation) to improve efficiency.
- Background in information retrieval or RAG (Retrieval-Augmented Generation) is a plus for building systems that augment LLMs with external knowledge.
ML & Programming Skills:
- Proficiency in Python and common data science libraries (pandas, NumPy, scikit-learn).
- Strong experience with deep learning frameworks such as PyTorch or TensorFlow for building NLP models.
- Ability to write efficient, clean code and debug complex model issues.

Data & Analytics:
- Solid understanding of data analytics and statistics.
- Experience in experimental design, A/B testing, and statistical hypothesis testing to evaluate model performance.
- Experience on how to build a representative benchmarking framework given business requirements for LLM.
- Comfortable working with large datasets, writing complex SQL queries, and using data visualization to inform decisions.

Deployment & Tools:
- Experience deploying machine learning models in production (e.g., using REST APIs or batch pipelines) and integrating with real-world applications.
- Familiarity with MLOps concepts and tools (version control for models/data, CI/CD for ML).
- Experience with cloud platforms (AWS, GCP or Azure) and big data technologies (Spark, Hadoop) for scaling data processing or model training is a plus.
- Hands-on experience with containerization (Docker) and orchestration (Kubernetes) for ML, as well as ML workflow tools (MLflow, Airflow).
Leadership & Communication:
- Demonstrated ability to lead technical projects and mentor junior team members.
- Strong communication skills to convey complex ML results to non-technical stakeholders and to document methodologies clearly.

Responsibilities:
- Lead end-to-end development of NLP and LLM models - from data exploration and model prototyping to validation and production deployment. This includes designing novel model architectures or fine-tuning state-of-the-art transformer models (e.g., BERT, GPT) to solve project-specific language tasks.
- Analyze large text datasets (Ukrainian and multilingual corpora) to extract insights and build robust training datasets.
- Guide data collection and annotation efforts to ensure high-quality data for model training.
- Develop and implement NLP algorithms for a range of tasks such as text classification, named entity recognition, semantic search, and conversational AI.
- Stay up-to-date with the latest research to apply transformer-based models, embeddings, and other modern NLP techniques in the solutions.
- Establish evaluation metrics and validation frameworks for model performance, including accuracy, factuality, and bias.
- Design A/B tests and statistical experiments to compare model variants and validate improvements.
- Deploy and integrate NLP models into production systems in collaboration with engineers - ensuring models are scalable, efficient, and well-monitored in a real-world setting.
- Optimize model inference and troubleshoot issues such as model drift or data pipeline bottlenecks.
- Provide technical leadership and mentorship to the NLP/ML team.
- Review code and research, uphold best practices in ML (version control, reproducibility, documentation), and foster a culture of continuous learning and innovation.
- Collaborate cross-functionally with product managers, software engineers, and MLOps engineers to align NLP solutions with product goals and infrastructure capabilities.
- Communicate complex data science concepts to stakeholders and incorporate their feedback into model development.

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.

Role Description

This is a full-time remote role for a Machine Learning Engineer. The Engineer will be responsible for developing and implementing machine learning algorithms, conducting pattern recognition, and utilizing neural networks and statistical analysis to optimize asset management.

Key Responsibilities

· Design, implement, and train computer vision models using PyTorch.

· Develop and maintain data loading and pre-processing algorithms, primarily written in Rust.

· Optimize and fine-tune models for performance, accuracy, and efficiency.

· Integrate the resulting models into our services and data processing pipelines.

· Define, implement, and evaluate custom metrics for ML experiments to measure success.

· Collaborate with domain experts to gather insights, interpret industry standards, and design machine-learning solutions aimed at automating processes and reducing manual labor.

Required skills

· 5+ years of experience in machine learning.

· Solid understanding of neural networks, especially CNNs and transformer-based vision models.

· Experience with training and optimizing large-scale models on GPUs.

· Familiarity with data processing libraries such as NumPy, Pandas, and OpenCV.

· Strong problem-solving and troubleshooting skills, with the ability to debug and optimize complex systems.

· Experience writing software in Rust and/or C++.

· A good understanding of linear algebra and Euclidian geometry.

· Ability to work independently and in a team environment

· Excellent problem-solving and analytical skills

· Master's or PhD in Computer Science, Engineering, or related field

Preferred skills

· Experience writing software in Rust.

· Familiarity with Kubernetes.

Welcome to King Group - a place where the best people from the IT and gambling industries meet to do amazing things together. We operate numerous projects in the iGaming sector in the markets of Ukraine, Europe and the USA, invest in venture startups, promising ideas and people.
 

One of our companies is a game studio that deals with the full cycle of iGaming product development. From idea to release, we combine creativity, modern technologies and deep analytics to create a unique gaming experience. Our mission is to excite, inspire and shape the future of the industry.

Our company is looking for a math expert who has a drive and passion (perhaps some experience) for games.

Key skills (it's not necessary to have all key skills, but more is better than less):

• Higher education in mathematics or related fields (related to research, analytics or data processing);
• Have a strong math background (especially probability theory, statistics, combinatorics);
• Advanced knowledge of MS Excel (statistical, mathematical functions);
• Be proficient at one (at least) programming language (Python is preferable);
• Knowledge of one of the CAS (Mathematica, Mathcad, Maxima);
• Have a strong math background (especially probability theory, statistics, combinatorics);
• Have previous experience in gaming industry or (and) have experience in playing slots (or any other probabilistic games (poker, blackjack, etc));
• Understand the time and memory complexity of your code;
• Be keen on details (Yes, it's really important at this position);
• Understanding OOP Concepts;
• Experience in developing mathematical models.
   

Nice to have:

• Experience in using git;
• Experience in using JIRA.
   

Responsibilities: 

• Prepare math for slot games;
• Discuss with business/ propose new game ideas/new feature ides;
• Implement game logic of new features, games;
• Gather games' statistics by precise calculations / running simulations of the games;
• Make games attractive for players from the math side.
   

Why we:

• Social Package;
• Medical care;
• Sick Days;
• Professional development support;
• Family-like atmosphere. You can check it out yourself ;)
• Great career prospects.
  
  Do you want to grow with us? Do you have the desire to take an active part in creating a product? Send your resume and let's get to know each other ;)

Machine Learning Engineer

Movadex is expanding its team and looking for a Machine Learning Engineer who’s ready to build smart, scalable AI solutions, shape the company’s ML strategy, and bring innovative ideas to life.

We work at the intersection of design, engineering, and data — helping businesses grow with products that actually make a difference.

What you’ll be doing

• Take the lead in developing and integrating AI/ML
• Collaborate with product and engineering teams to turn data into meaningful business insights;
• Strengthen Movadex’s internal AI/ML expertise and help shape our long-term tech vision;
• Explore new ways to apply machine learning across different teams — from marketing to customer success;
• Contribute to building a solid ML infrastructure and improving development workflows.

What we expect from you

• 3+ years of hands-on experience in AI/ML development;
• Strong command of Python and SQL;
• Solid knowledge of ML frameworks and real-world implementation experience;
• Deep understanding of supervised and unsupervised learning;
• Experience with time-series forecasting and data-driven decision making;

• Strategic thinking and readiness to take ownership of architectural decisions.

   

What We Offer:

• Flexible work setup: remote or hybrid, depending on your location.
• Competitive compensation and benefits.
• Resources for continuous learning: courses, conferences, certifications.
• Access to tools and environments that support experimentation and scale.
• Supportive team environment with strong values around growth and impact.