ML Tech Lead (wih GenAI)

Provectus

Medellín

On-site

COP 301,625,004 - 452,437,507

Full time

14 days+

Get a reply from this employer

Your resume and cover letter, tailored to exactly what they’re hiring for.

Get past ATS filters

Job summary

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.

Qualifications

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

Responsibilities

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

Skills

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

Tools

TensorFlow
PyTorch
scikit-learn
AWS

Job description

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.

Get your free, confidential resume review.

or drag and drop your file here.

Similar jobs

Similar jobs worth comparing

ML Tech Lead (GenAI)
ML Tech Lead (GenAI)

Provectus • Cali

On-site
COP 306,713,184 - 383,391,481
ML Tech Lead (wih GenAI)
ML Tech Lead (wih GenAI)

Provectus • Norte

On-site
COP 167,400,000 - 279,000,000
ML Tech Lead: Architect ML Systems & Mentorship
ML Tech Lead: Architect ML Systems & Mentorship

Provectus • Norte

On-site
COP 167,400,000 - 279,000,000
GenAI ML Tech Lead: Architect, Mentor, Hands-on Leader
GenAI ML Tech Lead: Architect, Mentor, Hands-on Leader

Provectus • Cali

On-site
COP 306,713,184 - 383,391,481
ML Solutions Architect (GenAI)
ML Solutions Architect (GenAI)

Provectus • Cali

Remote
COP 120,000,000 - 180,000,000
ML Tech Lead: Architecture & Mentorship in Production ML
ML Tech Lead: Architecture & Mentorship in Production ML

Provectus • Medellín

On-site
COP 301,625,004 - 452,437,507
ML Solutions Architect (GenAI)
ML Solutions Architect (GenAI)

Provectus • Norte

On-site
COP 187,447,000 - 374,895,000
SR MLOps Developer (Python), Colombia
SR MLOps Developer (Python), Colombia

CI&T • Norte

On-site
COP 30,000 - 70,000
Maternity and Parental leaves
Mobile services subsidy
Sick pay
+4
Machine Learning Engineer
Machine Learning Engineer

Capgemini Engineering • Colombia

On-site
COP 218,762,533 - 328,143,799
Stable Employment
Learning & Development
Language Training
+3
Machine Learning Engineer
Machine Learning Engineer

Capgemini Engineering • Colombia

On-site
COP 182,501,734 - 255,502,427
Stable Employment
Learning & Development
Language Training
+3