ML Tech Lead (GenAI)

Provectus; Cali; Presencial; COP 306.713.184 - 383.391.481; Jornada completa

Descripción de la vacante

A technology company in Colombia is seeking an ML Tech Lead to provide technical leadership and mentorship for their ML engineering team. This role involves guiding technical decisions, ensuring code quality, and developing a culture of technical excellence. The successful candidate should have deep expertise in ML and production ML systems, expertise in multiple ML frameworks, and a strong understanding of cloud platforms. This is a full-time position with a mid-senior level seniority.

Formación

• Advanced knowledge across multiple ML domains.
• Extensive experience building production-grade ML systems.
• Ability to design scalable, maintainable ML architectures.
• Strong understanding of ML infrastructure and operations.
• Experience with modern LLM-based applications.
• Exemplary coding standards and best practices.

Responsabilidades

• Set technical direction and standards for ML projects.
• Mentor junior and mid-level ML engineers.
• Contribute code to critical or complex components.
• Make architectural decisions for ML systems.
• Champion best practices in ML engineering.

Conocimientos

Deep ML expertise

Production ML

Architecture

MLOps

Code quality

Multiple ML frameworks

Cloud platforms

Data engineering

System design

Performance optimization

Herramientas

TensorFlow

PyTorch

Scikit-learn

AWS

Git

Descripción del empleo

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: Understanding of data pipelines and infrastructure
  • System design: Ability to design complex distributed systems
  • Performance optimization: Experience optimizing ML models and infrastructure
• 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.

Job Details

• Seniority level: Mid‑Senior level
• Employment type: Full‑time
• Job function: Engineering and Information Technology
• Industries: Transportation, Logistics, Supply Chain and Storage