sentiment analysis and entity extraction, and when half the industry was hiring data scientists without knowing why... They understand where this market is going because they’ve watched every shift from the inside.

They champion: - Deep Expertise - Thoroughness - Straight Talking - Inclusive Hiring - Proper Partnerships

They provide quality over quantity with an open, flexible and down to earth approach. In doing this they build teams that deliver results.

Their core markets include: - 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.

They've built D33P S1GNL, a proprietary talent intelligence engine. Instead of relying on profiles and keywords, it analyses what engineers actually ship across open-source ML projects. The code they write. The systems they contribute to. The trajectory of their work over time. For those who also publish research, it connects their engineering output to their academic footprint.... It’s how they find engineers that don’t appear in a keyword search. And it’s why their shortlists look different from everyone else’s.

They provide Retained, Permanent & Contract recruitment solutions, along with ML Market Intelligence.