Description
Summary:
Seeking a GenAI Tech Lead with expertise in Large Language Models and AWS Cloud services to oversee the development and deployment of AI solutions and manage a team of engineers.
Highlights:
1. Oversee development and deployment of cutting-edge AI solutions
2. Lead and mentor a team of ML engineers
3. Contribute code to critical or complex components
Medellín, Antioquia,Bogotá, Capital District,Cali, Valle del Cauca,Barranquilla,Bucaramanga, Santander
About project
Provectus helps companies adopt ML/AI to transform the ways they operate, compete, and drive value. The focus of the company is on building ML Infrastructure to drive end\-to\-end AI transformations, assisting businesses in adopting the right AI use cases, and scaling their AI initiatives organization\-wide in such industries as Healthcare \& Life Sciences, Retail \& CPG, Media \& Entertainment, Manufacturing, and Internet businesses.
We are seeking a highly skilled GenAI Tech Lead with a strong background in Large Language Models (LLMs) and AWS Cloud services. The ideal candidate will oversee the development and deployment of cutting\-edge AI solutions while managing a team of engineers. This leadership role demands hands\-on technical expertise, strategic planning, and team management capabilities to deliver innovative products at scale.
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
What We Offer:
* Long\-term B2B collaboration;
* Fully remote setup;
* A budget for your medical insurance;
* Paid sick leave, vacation, public holidays;
* Continuous learning support, including unlimited AWS certification sponsorship.
Interview stages:
* Recruitment Interview;
* Tech interview;
* HR Interview;
* HM Interview.