Work closely with business departments (Sales, Marketing, Products, Payments, Dealing) to understand their needs and translate these into practical, scalable, and robust machine learning solutions.
Work on such projects like LTV prediction, churn prediction, antifraud solutions, uplift modelling, GenAI-applications
Oversee current solutions, manage improvements if needed, expand the role of machine learning across organisation.
Implement new and improve current MLOps practices, laying the foundation for efficient and effective model development, deployment, and monitoring.
Implement new and support existing LLM projects (chatbots, knowledge base etc).

Great understanding of business and where ML solutions can fit and bring value
Technological stack
Python, PyTorch,, SQL (MSSQL, Postgres), ClickHouse, AWS (Sagemaker, EC2, EKS, EMR), Docker, FastApi, Kafka, Airflow
Establishing and maintaining MLOps practices, including version control for models, automated testing, and CI/CD for ML systems
Utilise AWS ML (or similar) services for developing and deploying models
General understanding of IT infrastructure, various data source types, development processes etc.
Great to have previous experience in applying data science tools to mobile apps, gaming or fintech
Intermediate level of English
Experience with LLMs is a huge plus (AWS Bedrock, langchain, langgraph, RAG, Agents, MCP)

Quarterly bonuses based on Company performance
Generous relocation package for the employee and their immediate family/partner
Medical Insurance Plan with coverage for the employee and their immediate family from day one
24 working days of annual leave
Yearly reimbursement of travel expenses for the employee and family's flight home
Corporate events and team building activities
Udemy Business unlimited membership & language training courses
Professional and personal development opportunities in a fast-growing environment

Machine Learning Engineer

Key skills