ML Tech Lead (wih GenAI)

Provectus

Medellín

Presencial

COP 301.625.004 - 452.437.507

Jornada completa

14 días+

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Descripción de la vacante

A tech innovation firm is seeking a skilled ML Tech Lead to guide technical decisions and mentor a dynamic engineering team in Medellín, Colombia. In this role, you will set direction for ML projects, architecture, and ensure top-notch code quality while also providing mentorship to junior engineers. Ideal candidates should have profound knowledge in ML domains and hands-on experience with production systems. Join us in building a culture of technical excellence in a collaborative environment.

Formación

  • Advanced knowledge across multiple ML domains.
  • Extensive experience building production-grade ML systems.
  • Ability to design scalable ML architectures.

Responsabilidades

  • Provide technical leadership for the ML engineering team.
  • Mentor junior and mid-level ML engineers.
  • Contribute code to critical components.

Conocimientos

Deep ML Expertise
Production ML systems
Multiple ML Frameworks
Performance Optimization
Clean Code
Testing practices

Herramientas

TensorFlow
PyTorch
scikit-learn
AWS

Descripción del empleo

1 month ago Be among the first 25 applicants

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

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.

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