We are looking for a Machine Learning Engineer to join our team and drive the development of a scalable machine learning framework and tooling.

You will play a key role in enabling efficient collaboration between data scientists, data engineers and cloud architects. You´ll also help build GenAI-centric tools that improve the ML lifecycle through automation, optimization and observability.

RESPONSIBILITIES
- Design, build and maintain a robust framework to support machine learning projects at scale
- Act as a technical bridge between data science, engineering and cloud infrastructure teams
- Collaborate on the development and deployment of GenAI applications and agents such as LLM pipelines and image generation models
- Deploy models using containerized and serverless infrastructure such as Docker, Kubernetes and Azure Functions

REQUIREMENTS
- Proven experience in MLOps and DevOps practices across the ML lifecycle
- Hands-on experience with cloud platforms, especially Azure: Azure ML, Functions, Storage
- Familiarity with Orchestration of ML pipelines and experiments with MLOps tooling such as MLflow, Vertex AI, Azure Machine Learning, Databricks Workflows and SageMaker
- Solid understanding of model deployment using Docker, Kubernetes and serverless technologies
- Strong software engineering background: Python, CI/CD, testing frameworks

NICE TO HAVE- Experience with GenAI technologies such as Agentic workflows: LangChain, OpenAI tools, custom agents
- Working knowledge of the MCP server or similar scalable serving architectures
- Exposure to retrieval-augmented generation (RAG) or vector database integrations
- Experience working with infrastructure-as-code tools for deploying ML systems on the cloud

WE OFFER- Private health insurance
- EPAM Employees Stock Purchase Plan
- 100% paid sick leave
- Referral Program
- Professional certification
- Language courses