This document provides detailed guidance to staffing partners and vendors for identifying suitable candidates for the ML/AI Engineer and ML Lead positions.
Over the past several interview cycles, we have observed that many candidates have resumes containing modern AI technologies (e.g., Vertex AI, Gemini, ADK, LangChain, RAG), but are unable to demonstrate hands-on implementation experience during technical interviews.
The goal of this document is to clearly define the expected technical competencies and reduce profile mismatches.
2. Role Overview
We are looking for hands-on AI Engineers, not architects or delivery managers.
The ideal candidate should be capable of:
- Designing production-grade AI solutions
- Developing AI applications using Python
- Building and deploying AI Agents
- Implementing RAG pipelines
- Working extensively on Google Cloud Platform
- Mentoring junior engineers
- Working directly with US stakeholders
This is not a research role, nor a project management role.
3. Candidate Profile
Requirement
Preferred
Experience
612 years
AI/ML Experience
4+ years
GenAI Experience
2+ years
Python
Solid hands-on
GCP
Strong hands-on
Client Communication
Required
Team Leadership
Preferred for ML Lead
4. Mandatory Technical Skills
A. Python Development (Mandatory)
Candidates should be actively writing production code.