ML hiring built on code, not claims
Specialist AI/ML recruitment across the full stack… from ML Systems to Applied Research.
Seed to Series D
14 years in AI/ML. One focus.
We’ve placed engineers, researchers, and ML leads at some of the most ambitious companies in North America, the UK, and Europe since 2012. We know what good looks like because we’ve been in this space longer than most of the companies hiring in it.
Current roles across the ML stack:
-
Hardware Engineering
Semiconductors, AI accelerators, photonics, IC design, packaging, reliability and test. The physical layer of AI.
-
Cloud & HPC Architecture
Systems and infrastructure architects building the compute layer. Cloud, hybrid, HPC, and performance engineering.
-
Infrastructure & Operations
MLOps, SRE, DevOps, and platform engineers. The people who keep ML systems running at scale.
-
Software Engineering
Backend, distributed systems, compilers, and kernel specialists. The engineers building the runtime, not just the model.
-
AI & Machine Learning
Applied researchers, research engineers, ML engineers. Training, serving, optimization, and everything in between.
-
Product Management & Leadership
Technical PMs and product leaders who can translate between research teams and business outcomes.
Precise hiring for the teams that can’t afford to get it wrong.
The ML talent market is opaque. We’ve built the infrastructure to see through it.
D33P S1GNL is our proprietary talent intelligence engine. It analyses contributor activity across 1,800+ open-source ML repositories, tracking who’s building what, where engineering effort is concentrating, and which skills are emerging before they show up on a CV.
It’s how we find engineers that don’t appear in a keyword search. And it’s why our shortlists look different from everyone else’s.
Got a hard ML hire?
We work retained and contingency with Seed-to-Series-D companies. If the role matters, let’s talk.
Or leave us a message and we will get back to you