Jobs

We are looking for a mid-to-senior Data Scientist who is eager to proactively identify opportunities to improve and automate our business using data science and machine learning. You will work within a small, dedicated team of data scientists collaborating closely with backend engineers, other departments, and end users, while being part of a larger ecosystem of trading and technology experts.

In this role, you will design, develop, and optimize predictive models, implement anomaly detection systems, and participate in building production-grade machine learning solutions that directly impact trading and operational processes. You’ll also get hands-on experience with (or apply your existing knowledge of) high-performance architectures, including Kafka, serverless functions, databases, CI/CD pipelines, Kubernetes, and Docker.

Key Responsibilities:

• Develop and refine mathematical and statistical models for predicting sports and e-sports outcomes.
• Communicate with end users, collect feedback, and build technical solutions based on it.
• Apply machine learning to improve trading strategies, automate workflows, and detect anomalies.
• Proactively identify opportunities to use data science for business optimization and process automation.
• Perform large-scale historical data analysis to generate insights and improve model performance.
• Collaborate with backend engineers to build and maintain production machine learning systems.
• Research and prototype new methods for expanding into new sports and markets.

KPIs for This Role:

• Delivery of production-ready machine learning models and pipelines for trading within agreed timelines.
• Improvement in model accuracy and reliability, measured against established benchmarks.
• Reduction of manual intervention in trading workflows through automation initiatives.
•  

Requirements:

• 3+ years of experience in data science, analytics, or a related field.
• Proficiency in Python (pandas, numpy, scikit-learn, etc.) and working with databases.
• Strong knowledge of statistical modeling, probability, and machine learning techniques (Supervised Learning, Unsupervised Learning).
• Experience with XGBoost/LightGBM.
• Experience with large-scale data analysis and building actionable insights.
• Ability to work collaboratively in a cross-functional team and communicate results clearly.

Nice-to-Have:

• Experience in the sports or betting industry.
• Experience with PyTorch/Tensorflow.
• Familiarity with real-time data processing (Kafka, streaming systems).
• Exposure to building data pipelines and integrating ML models into production systems.
• Knowledge of advanced ML techniques (e.g., ensemble methods, time-series forecasting, anomaly detection).

What We Offer:

• Work on high-impact projects in the fast-growing sports and e-sports betting industry.
• A collaborative environment within a skilled team of data scientists and engineers.
• Flexibility: Hybrid work with remote options.
• Opportunities to shape our analytics and machine learning ecosystem and see your ideas implemented in production.

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 Object tracking, Visual-Inertial Odometry (VIO) and sensor fusion. 

We consider engineers at Middle+ and Senior levels - tasks and responsibilities will be adjusted accordingly. 

Required Qualifications: 

• 2+ years of hands-on experience with classical computer vision
• Understanding of geometrical computer vision principles 
• Hands-on experience in implementing low-level CV algorithms
• Proficiency in C++ 
• Experience with Linux 
• Experience with Object tracking and detection tasks 
• Ability to quickly navigate through recent research and trends in computer vision. 
• Familiarity with neural networks and common CV frameworks/libraries (OpenCV, NumPy, PyTorch, ONNX, Eigen, etc.) 

Nice to Have: 

• Practical experience with SLAM and/or Visual-Inertial Odometry (VIO) 
• Experience with Python 
• Experience with sensor fusion. 

About us:
Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with the organization of the first Data Science UA conference, setting the foundation for our growth. Over the past 9 years, we have diligently fostered one of the largest Data Science & AI communities in Europe.

About the role:
We seek an experienced AI/ML Team Leader to join our Client’s startup team. As the Technical Lead, you will start with individual technical contributions and later will take an engineering manager role for the hiring team. You will create cutting-edge end-to-end AI camera solutions, effectively engage with customers and partners to grasp their requirements and ensure project success, overseeing from inception to completion.

Requirements:
- Proven leadership experience with a track record of managing and developing technical teams;
- Excellent customer-facing skills to understand and address client needs effectively;
- Master's Degree in Computer Science or related field (PhD is a plus);
- Solid grasp of machine learning and deep learning principles;
- Strong experience in Computer Vision, including object detection, segmentation, tracking, keypoint/pose estimation;
- Proven R&D mindset: capable of formulating and validating hypotheses independently, exploring novel approaches, and diving deep into model failures;
- Proficiency in Python and deep learning frameworks;
- Practical experience with state-of-the-art models, including different versions of YOLO and Transformer-based architectures (e.g., ViT, DETR, SAM);
- Expertise in image and video processing using OpenCV;
- Experience in model training, evaluation, and optimization;
- Fluent written and verbal communication skills in English.

Would be a plus:
- Experience applying ML techniques to embedded or resource-constrained environments (e.g. edge devices, mobile platforms, microcontrollers);
- Ideally, you have led projects where ML models were optimized, deployed, or fine-tuned for embedded systems, ensuring high performance and low latency under hardware limitations.

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

We’re looking for a Senior Data Scientist to help shape how our clients build and scale AI solutions on AWS. In this role, you’ll develop and deploy cutting-edge generative AI models on SageMaker – from model training and fine-tuning to optimized deployment – guiding customers from ideation to production through proof of concept. You’ll work closely with startup founders, technical leaders, and account teams to create scalable, high-impact AI solutions that drive real business value.

Responsibilities:

• 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 Data Engineering, DevOps, and MLOps teams to integrate models into production pipelines and workflows.

Requirements:

• 4+ years of experience in machine learning or data science roles, with deep learning (NLP, LLMs) expertise.
• 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.
• Strong experience deploying ML solutions on AWS cloud infrastructure and familiarity with MLOps best practices.
• Excellent communication skills and ability to work directly with customers in a consulting capacity.
• 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.

Quantum is a global technology partner delivering high-end software products that address real-world problems.

We advance emerging technologies for outside-the-box solutions. We focus on Machine Learning, Computer Vision, Deep Learning, GIS, MLOps, Blockchain, and more.

Here at Quantum, we are dedicated to creating state-of-art solutions that effectively address the pressing issues faced by businesses and the world. To date, our team of exceptional people has already helped many organizations globally attain technological leadership.

We constantly discover new ways to solve never-ending business challenges by adopting new technologies, even when there isn’t yet a best practice. If you share our passion for problem-solving and making an impact, join us and enjoy getting to know our wealth of experience!

About the position

Quantum is expanding the team and has brilliant opportunities for a Data Science Engineer. The client is a technological research company that utilizes proprietary AI-based analysis and language models to provide comprehensive insights into global stocks in all languages. Our mission is to bridge the knowledge gap in the investment world and empower investors of all types to become “super-investors.”

Through our generative AI technology implemented into brokerage platforms and other financial institutions’ infrastructures, we offer instant fundamental analyses of global stocks alongside bespoke investment strategies, enabling informed investment decisions for millions of investors worldwide.

Must have skills:

• At least 5 years of commercial experience in Data Science
• Strong knowledge of linear algebra, calculus, statistics, and probability theory
• Proficiency in algorithms and data structures
• Experience with Machine Learning libraries (NumPy, SciPy, Pandas, Scikit-learn)
• Experience with at least one Deep Learning framework (TensorFlow, Keras, or PyTorch)
• Knowledge of modern Neural Network architectures
• Experience in developing solutions with LLMs
• Experience with Cloud Computing Platforms (AWS, Google Cloud, or Azure)
• Practical experience with Docker
• Experience with SQL
• Strong understanding of Object-Oriented Programming (OOP) principles
• Hands-on experience in building solutions for financial domain
• At least an Upper-Intermediate level of English (spoken and written)

Would be a plus:

• Experience with MLOps solutions
• Basic understanding of Big Data concepts
• Experience in classical Computer Vision algorithms
• Participation in Kaggle competitions

Your tasks will include:

• Full-cycle data science projects
• Data analysis and data preparation
• Development of NLP/Deep Learning / Machine Learning; Developing models and deploying them to production
• Sometimes, this will require the ability to implement methods from scientific papers and apply them to new domains

We offer:

• Delivering high-end software projects that address real-world problems
• Surrounding experts who are ready to move forward professionally
• Professional growth plan and team leader support
• Taking ownership of R&D and socially significant projects
• Participation in worldwide tech conferences and competitions
• Taking part in regular educational activities
• Being a part of a multicultural company with a fun and lighthearted atmosphere
• Working from anywhere with flexible working hours
• Paid vacation and sick leave days

Join Quantum and take a step toward your data-driven future.

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

About us

Kyivstar.Tech is a Ukrainian hybrid IT company and a resident of Diia.City.

We are a subsidiary of Kyivstar, one of Ukraine's largest telecom operators.

Our mission is to change lives in Ukraine and around the world by creating technological solutions and products that unleash the potential of businesses and meet users' needs.

Over 500+ KS.Tech specialists work daily in various areas: mobile and web solutions, as well as design, development, support, and technical maintenance of high-performance systems and services.

We believe in innovations that truly bring quality changes and constantly challenge conventional approaches and solutions. Each of us is an adherent of entrepreneurial culture, which allows us never to stop, to evolve, and to create something new.

What you will do 

• 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 our 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 the model development process.

Qualifications and experience needed 

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.

• 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 in building 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.

A plus would be 

LLM training & evaluation experience:

• Experience with tokenizer development, SFT, and RLHF techniques.

• Knowledge of model safety: toxicity, hallucinations, ethical considerations, and LLM guardrails.

Research & Community:

• Publications in NLP/ML conferences or contributions to open-source NLP projects.

• Active participation in the AI community or demonstrated continuous learning (e.g., Kaggle competitions, research collaborations) indicating a passion for staying at the forefront of the field.

Domain & Language Knowledge:

• Familiarity with the Ukrainian language and cultural context for model training and evaluation.

MLOps & Infrastructure:

• Hands-on experience with containerization (Docker) and orchestration (Kubernetes) for ML, as well as ML workflow tools (MLflow, Airflow).

• Experience in working alongside MLOps engineers to streamline the deployment and monitoring of NLP models.

Problem-Solving:

• Creative mindset for tackling open-ended AI challenges.

• Comfort in fast-paced R&D environments with evolving priorities.

What we offer

• Office or remote — it’s up to you. You can work from anywhere, and we will arrange your workplace.

• Remote onboarding.

• Performance bonuses.

• We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners.

• Health and life insurance.

• Wellbeing program and corporate psychologist.

• Reimbursement of expenses for Kyivstar mobile communication.

On behalf with our customer we are seeking for Data Scientist for customer-facing projects that combine data science with deep knowledge and understanding of machine learning and big data technologies to create solutions for customers’ challenges and needs, defining and developing appropriate technical and business solutions.

Our customer is the leading provider of AI-based Big Data analytics.

They are dedicated to helping financial organizations combat financial crimes through money laundering and facilitating malicious crimes such as terrorist financing, narco-trafficking, and human trafficking which negatively impact the global economy.

Key Responsibilities

• Deliver successful deployment and Pilots
• Manage and design the Customer-specific technical solution throughout the project life cycle
• Technical leadership of Data Science & Engineering aspects and team members including partners
• Work on various data sources and apply sophisticated feature engineering capabilities
• Bring and use business knowledge
• Extract insights and actionable recommendations from large volumes of data and Investigate anomalies in Big Data
• Build and manage technical relationships with customers and partners
• Provide product requirements input to the Product Management team
• Train the customers on the system – system usage and monitoring aspects
• Travel to customer locations both domestically and abroad

Position Requirements

• 3+ years of experience as a Data Engineer, Data Scientist, or Big Data Developer
• Hands-on experience with Apache Spark, Python/PySpark, and SQL
• Familiarity with Hadoop ecosystem (Hive, Impala, HDFS, Sqoop) and data pipeline optimization
• Practical experience building or integrating AI agents and working with LLMs
• Strong skills in data transformation, ML feature engineering, and analytics for financial services
• Experience with workflow automation tools (Airflow, MLflow, n8n) and version control (GIT)
• Ability to work with customers, train teams, and deliver technical solutions
• English level B2 and higher

What we can offer you

• Remote work from Ukraine or EU countries with flexible schedule
• Accounting support & consultation
• Opportunities for learning and developing on the project
• 20 working days of annual vacation
• 5 days paid sick leaves/days off; state holidays
• Provide working equipment

We are looking for a Data Scientist to support a Data & AI team. The role is focused on developing scalable AI/ML solutions and integrating Generative AI into evolving business operations.

About the Role

As a Data Scientist, you will:

• Collaborate with Product Owners, Data Analysts, Data Engineers, and ML Engineers to design, develop, deploy, and monitor scalable AI/ML products.
• Lead initiatives to integrate Generative AI into business processes.
• Work closely with business stakeholders to understand challenges and deliver tailored data-driven solutions.
• Monitor model performance and implement improvements.
• Apply best practices in data science and ML for sustainable, high-quality results.
• Develop and fine-tune models with a strong focus on accuracy and business value.
• Leverage cutting-edge technologies to drive innovation and efficiency.
• Stay updated on advancements in AI and data science, applying new techniques to ongoing processes.

About the Candidate

We are looking for a professional with strong analytical and technical expertise.

Must have:

• 3+ years of hands-on experience in Data Science and ML.
• Experience with recommendation systems and prescriptive analytics.
• Proficiency in Python, SQL, and ML libraries/frameworks.
• Proven experience developing ML models and applying statistical methods.
• Familiarity with containerization and orchestration tools.
• Excellent communication skills and strong command of English.
• Bachelor’s or Master’s degree in Computer Science, Statistics, Physics, or Mathematics.

Nice to have:

• Experience with Snowflake.
• Exposure to Generative AI and large language models.
• Knowledge of AWS services.
• Familiarity with NLP models (including transformers).

Join Our Fast-Growing iGaming Company!
Take the lead in ensuring high-quality, seamless user experiences for thousands of players worldwide. At 7Rings Gaming, we create slot games from scratch — from the first idea to the formulas that shape RTP, volatility, and bonus systems.
We’re looking for a Game Mathematician to design models, balance games, and turn numbers into fun experiences for players.

What You’ll Do:

• Design mathematical models (RTP, volatility, hit frequency, distribution curves).
• Balance games: from payout tables to bonus systems and free spins.
• Write simulations, analyze results, and find optimal solutions.

• Collaborate closely with game designers and developers.

   

We’re Looking For Someone Who:

• Has 3+ years of experience in game mathematics or game design with a strong math focus.
• Understands slot mechanics, RTP, volatility, and bonus systems.
• Is proficient with Excel / Google Sheets.
• Pays attention to detail but also thinks creatively.

• Has basic programming knowledge (advanced level is a big plus).

   

You’ll Be a Great Fit If You:

• Think like a player but analyze like a mathematician.
• Want to experiment and create new things instead of copy-pasting old features.

• Get excited by numbers, formulas, and challenges.

   

What We Offer:

• Flexible, remote-friendly work environment.
• Formal employment with paid sick leave (7 days/year) and annual vacation (21 days/year).
• A collaborative and innovative team culture where your ideas matter.
• The opportunity to shape high-performing games in a growing company.
• Personal attention and support for every team member.

The role covers architecture, production deployment, and continuous performance monitoring.

Responsibilities:
Architect, fine-tune, and evaluate advanced ML models (including large language models) to support modular intelligent behavior.
Build reliable end-to-end ML workflows: data ingestion, feature preparation, model training, deployment, and monitoring.
Develop and maintain scalable serving infrastructure using containers (Docker, Kubernetes) and integrate with backend services.
Establish evaluation pipelines, run A/B experiments, and track performance metrics to ensure model effectiveness.
Guarantee reproducibility, compliance, and transparency across the full ML lifecycle.
Work with backend teams to define service SLAs and optimize real-time inference.
Mentor teammates and help shape engineering best practices.

Requirements:
5+ years of experience as an ML Engineer or applied researcher with hands-on deployment of production models.
Advanced Python skills with strong knowledge of ML frameworks (PyTorch, TensorFlow) and modern LLM tooling (e.g. HuggingFace).
Proficiency in MLOps: Docker, Kubernetes, model serving frameworks (Triton, FastAPI), CI/CD automation.
Familiarity with data pipelines, SQL, and cloud ML platforms (AWS, GCP, Azure).
Strong grasp of experimentation, A/B testing, and ML performance measurement.
Collaborative mindset, comfortable working with product, data, and engineering teams.

Preferred:
Experience with conversational AI, retrieval-augmented generation, or orchestrating multi-model systems.
Knowledge of vector search technologies (FAISS, Pinecone) and modern embedding methods.
Understanding of prompt design and RLHF approaches.
Startup background and ability to thrive in fast-changing environments.

What We Offer:
Competitive salary 
Direct collaboration with seasoned founders and industry experts.
Fast-paced environment with minimal bureaucracy.
Opportunity to shape cutting-edge AI applications in a high-impact domain.

Work format: Remote
Employment type: Full-time
 

Responsibilities

• Collect, clean, and analyze structured and unstructured data.
• Build predictive and statistical models to support data-driven decision-making.
• Develop and validate machine learning models for various domains (NLP, CV, recommendation systems, etc.).
• Perform exploratory data analysis (EDA), visualization, and feature engineering.
• Present findings and insights to both technical and non-technical stakeholders.

• Collaborate with engineers and product teams to deploy models into production.

   

Requirements

• Strong knowledge of Python and data science libraries (pandas, NumPy, scikit-learn, matplotlib, seaborn).
• Experience with statistical modeling, hypothesis testing, and A/B experiments.
• Hands-on experience with at least one ML/DL framework (PyTorch, TensorFlow, Keras).
• Solid understanding of SQL and experience with relational databases.
• Familiarity with cloud platforms (AWS, GCP, Azure) or big data tools (Spark, Hadoop).
• Strong problem-solving and analytical thinking skills.
• English level B2 or higher — ability to work in an international team.

Nice to have

• Experience in NLP, Computer Vision, or Generative AI projects.
• Familiarity with MLOps tools (MLflow, Airflow, W&B).
• Experience with NoSQL databases (MongoDB, ElasticSearch).
• Participation in Kaggle competitions or open-source projects.
• Background in business intelligence tools (Tableau, Power BI, Looker).

We offer

• Remote-first work with international projects.
• Diverse tasks across different domains (finance, healthcare, e-commerce, AI-driven solutions).
• Competitive compensation package.
• Growth opportunities towards Senior/Lead Data Scientist or ML Engineer roles.

We are looking for a Machine Learning Engineer (MLE) to design, build, and productionize ML evaluation and automation pipelines that support large-scale model development workflows.

The role involves working closely with algorithm developers, ML researchers, and product teams to build robust and scalable systems that automate model evaluations, manage distributed data processing, integrate human-in-the-loop validation processes, and produce actionable evaluation metrics. This position offers full ownership over the system’s architecture, implementation, scalability, and operational robustness, enabling efficient and rapid ML experimentation at scale.

Requirements

Must Have

• B.Sc. in Computer Science, Software Engineering, or a related technical field
• 3+ years of production-level Python development
• 3+ years building ML pipelines, data processing systems, or model evaluation infrastructure
• Strong system design skills and hands-on experience building distributed, scalable systems
• Experience with cloud compute platforms (Preferably Azure) — compute, storage, and networking
• Proficiency with:
  • Containerized workloads (Docker, Kubernetes)
  • SQL / NoSQL databases
  • Experience integrating data annotation platforms or human labeling workflows
  • Strong ownership mindset, able to independently design, build, and operate complex ML infra systems

Strong Advantage

• Experience with Computer Vision workloads and ML inference pipelines
• Experience building ML serving infrastructure and model deployment systems
• Familiarity with ML experiment tracking tools (Weights & Biases, ClearML, MLflow, etc.)
• Experience with video processing pipelines and encoding technologies
• Familiarity with cloud-native monitoring and observability stacks

Bonus

• Prior experience building evaluation or benchmarking pipelines for ML models
• Experience designing quality evaluation workflows for ML-based products
• Experience working in ML-heavy product companies or applied AI domains

Responsibilities

• Design and implement end-to-end ML evaluation pipelines supporting large-scale model assessments
• Build distributed data processing pipelines for ML inference, pre-processing, post-processing, and data transformation tasks
• Integrate human-in-the-loop annotation and validation systems as part of the evaluation workflow
• Design and implement scalable job orchestration, task dispatchers, and worker-based architectures for parallel ML workloads
• Manage storage, indexing, and retrieval of intermediate and final data artifacts
• Develop monitoring, logging, alerting, and observability for the entire pipeline
• Collaborate with algorithm and research teams to define flexible and reusable infrastructure components
• Automate manual and ad-hoc processes into robust, production-grade workflows
• Optimize resource utilization and ensure cost-effective pipeline operations.

Why this role

• Full ownership of designing critical ML infrastructure from the ground up
• Direct impact on ML development velocity and model quality
• Work with experienced ML researchers and engineers on production-grade systems
• Exposure to real-world applied AI workflows, cloud-scale systems, and automation challenges

What we offer

• Competitive salary range
• Medical insurance
• Paid vacation and sick leaves
• MultiSport card
• Top equipment kit, co-workings
• Hybrid set of works (Office location: Warsaw)
• Collaborative and innovative work environment
• Career growth and development opportunities
• A chance to work with giants of the sports industry

About the project

Our partner leads the industry in generating dynamic sports videos for every digital destination. Their cutting-edge AI and Machine Learning technologies analyse live sports broadcasts from over 250 leagues and broadcast partners, including iconic names like the NBA, NHL, ESPN, FIBA and Bundesliga, to create personalized, short-form videos in real-time.

The solution empowers media rights owners to unlock new revenue streams and deliver a tailored fan experience across every digital platform. Join the high-profile Engineering team and discover the forefront of sports contents innovation.

QA Madness is a European IT service company that focuses strongly on QA and cybersecurity. The company was founded in 2013 and is headquartered in Poland.

Currently, we are searching for an experienced  Machine Learning Engineer (Microsoft Azure) to become a great addition to our team. Currently, our client is looking for a  Machine Learning Engineer to become a great addition to their team.

Responsibilities:

• Design data science, statistical, machine learning and deep learning systems that influence millions of players;
• Implement and optimize appropriate ML algorithms and tools for time series and tabular data;
• Transform data science prototypes into full-scale products, while deploying and monitoring ML models;
• Run live tests and experiments;
• Train and retrain systems when necessary;
• Create or extend existing ML libraries and frameworks;
• Collaborate with other scientists, engineers, architects and analysts spread across several countries.

Required Skills:

• Strong experience with Python and data analysis libraries;
• Solid hands-on experience with MLOps in Azure environments;
• Hands-on experience with one or more DL frameworks (PyTorch, TensorFlow, Keras, JAX);
• Knowledge of MLOps tools (MLflow, W&B, Airflow);
• Background in NLP, Computer Vision, or Generative AI (one or more areas);
• Strong experience with MLFlow for tracking experiments and managing ML artifacts;
• Familiarity with databases (SQL/NoSQL);
• Practical knowledge of Docker and version control (Git);
• Upper-intermediate English level.

Please note, this job is a full-time position, and it is relevant only if you meet all requirements. Any candidate who fails to meet the requirements will not be considered for the job.

QA Madness is a European IT service company that focuses strongly on QA and cybersecurity. The company was founded in 2013 and is headquartered in Poland. 
Currently, we are searching for an experienced  Machine Learning Engineer (Microsoft Azure) to become a great addition to our team. Currently, our client is looking for a  Machine Learning Engineer to become a great addition to their team.   

Responsibilities: 
Design data science, statistical, machine learning and deep learning systems that influence millions of players; 
Implement and optimize appropriate ML algorithms and tools for time series and tabular data; 
Transform data science prototypes into full-scale products, while deploying and monitoring ML models; 
Run live tests and experiments; Train and retrain systems when necessary; Create or extend existing ML libraries and frameworks; 
Collaborate with other scientists, engineers, architects and analysts spread across several countries. 

Required Skills: 
Strong experience with Python and data analysis libraries; 
Solid hands-on experience with MLOps in Azure environments; 
Hands-on experience with one or more DL frameworks (PyTorch, TensorFlow, Keras, JAX); 
Knowledge of MLOps tools (MLflow, W&B, Airflow); 
Background in NLP, Computer Vision, or Generative AI (one or more areas); Strong experience with MLFlow for tracking experiments and managing ML artifacts; 
Familiarity with databases (SQL/NoSQL); 
Practical knowledge of Docker and version control (Git); 
Upper-intermediate English level. 

Please note, this job is a full-time position, and it is relevant only if you meet all requirements. Any candidate who fails to meet the requirements will not be considered for the job. 
Your application will be considered only once you have completed the questionnaire and uploaded your CV in English. (Click on the hyperlink or copy link into your Internet browser.)
 

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.