Our Process

We take time to understand your stack, workflows, team structure, and the real challenges behind the hire.
This ensures we target the right talent from day one.

We assess candidates on:

• Production‑grade MLOps experience
• Model deployment and CI/CD for ML
• LLM/RAG engineering capability
• Cloud and infrastructure fundamentals
• Tooling alignment (Kubernetes, MLflow, Terraform, Ray, LangChain, etc.)

This filters out noise and surfaces only the strongest engineers

You receive a curated shortlist with:

• Technical summaries
• Stack alignment
• Relevant project experience
• Availability and salary/day‑rate expectations

No fluff. No volume. Just the right people

We streamline scheduling, prep candidates, and ensure a smooth, efficient process that respects your time.

We manage expectations, negotiate fairly, and ensure a seamless transition into your team.

We stay close after placement — especially for contractors — to ensure delivery, stability, and long‑term success.