Machine Learning Engineer (Remote)

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. Utilise AWS ML (or similar) services for developing and deploying models. General understanding of IT infrastructure, data source types, and development processes. Experience with LLMs is a huge plus (AWS Bedrock, langchain, langgraph, RAG, Agents, MCP).

Work closely with business departments to understand needs and translate them into ML solutions. Work on projects like LTV prediction, churn prediction, antifraud, uplift modelling, and GenAI applications. Oversee current solutions, manage improvements, and expand the role of machine learning. Implement and improve MLOps practices for model development, deployment, and monitoring. Implement and support LLM projects (chatbots, knowledge base).