ML Tech Lead (GenAI)

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.