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
- 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:

📌 ML Tech Lead (Cali)
🏢 Provectus
📍 Cali