**ML Tech Lead** ================ Colombia,Medellín, Antioquia,Bogotá, Capital District,Cali, Valle del Cauca,Barranquilla,Bucaramanga, Santander,Bucaramanga Metropolitan Area **About project** As an ML Tech Lead, you'll provide technical leadership and mentorship for our ML engineering team in Colombia. You'll guide technical decisions, ensure code quality, mentor engineers, and help build a culture of technical excellence. While this is not a people\-management role, you'll serve as the technical anchor and go\-to expert for the team. **Core Responsibilities:** * 1\. 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 * 2\. 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 * 3\. 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:** * 1\. 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 * 2\. 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 * 3\. 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