Companies Provectus ML Tech Lead (GenAI, AWS)

About the role

Provectus

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.
  • Ready to apply to Provectus?
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