ML Tech Lead (GenAI, AWS)

Responsibilities: Technical Leadership (40%)

• Set technical direction and standards for ML projects

• Make architectural decisions for ML systems

• Review and approve technical designs

• Identify and address technical debt

• Champion best practices in ML engineering

• Troubleshoot complex technical challenges

• Evaluate and introduce new technologies and tools

Mentorship & Team Development (35%)

• Mentor junior and mid-level ML engineers (2-5 engineers)

• Conduct technical code reviews

• Provide guidance on technical problem-solving

• Help engineers debug complex issues

• Create learning opportunities and growth paths

• Share knowledge through workshops and documentation

• Build technical competency across the team

Hands-On Technical Work (25%)

• Contribute code to critical or complex components

• Build proof-of-concepts for new approaches

• Tackle highest-risk technical challenges

• Develop reusable ML accelerators and frameworks

• Maintain technical credibility through active coding

Requirements: ML Engineering Excellence

• Deep ML Expertise: Advanced knowledge across multiple ML domains

• Production ML: Extensive experience building production-grade ML systems

• Architecture: Ability to design scalable, maintainable ML architectures

• MLOps: Strong understanding of ML infrastructure and operations

• LLM Systems: Experience with modern LLM-based applications and RAG

• Code Quality: Exemplary coding standards and best practices

Technical Breadth

• Multiple ML Frameworks: Proficiency across TensorFlow, PyTorch, scikit-learn

• Cloud Platforms: Advanced AWS experience, familiarity with others

• Data Engineering: Understanding of data pipelines and infrastructure

• System Design: Ability to design complex distributed systems

• Performance Optimization: Experience optimizing ML models and infrastructure

Software Engineering

• Clean Code: Writes exemplary, maintainable code

• Testing: Champions testing practices (unit, integration, ML-specific)

• Git & Collaboration: Advanced Git workflows and collaboration patterns

• CI/CD: Experience building and maintaining ML pipelines

• Documentation: Creates clear, comprehensive technical documentation

What We Offer: Long-term B2B collaboration;

Fully remote setup;

A budget for your medical insurance;

Paid sick leave, vacation, public holidays;

Continuous learning support, including unlimited AWS certification sponsorship.

Interview stages: Recruitment Interview;

Tech interview;

HR Interview;

HM Interview.