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ML Tech Lead

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Provectus

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Location:
Colombia, Medellín ▼

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

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.

Job Responsibility:

  • 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
  • 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
  • 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:

  • 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
  • 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
  • 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

Additional Information:

Job Posted:
December 11, 2025

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