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
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
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses.
These tools assist our recruitment team but do not replace human judgment.
Final hiring decisions are ultimately made by humans.
If you would like more information about how your data is processed, please contact us.
Seniority level
Mid‐Senior level
Employment type
Full‐time
Job function
Engineering and Information Technology
Industries
Transportation, Logistics, Supply Chain and Storage
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📌 Ml Tech Lead (Wih Genai) (Huila)
🏢 Provectus
📍 Huila