AI & Machine Learning
Hire AI & Machine Learning Engineers
The teams behind AI features that ship.
Most AI hiring goes wrong at the same point. A team is brought in to build a model, when what the business actually needed was a feature that happens to use one — with the retrieval, evaluation, guardrails and fallback behaviour that makes it safe to put in front of a customer.
The engineers here have shipped that second thing. That means treating a confident wrong answer as the default failure mode, measuring quality against something better than a demo, and knowing which problems do not need a model at all.
AI/ML Engineers
Machine learning engineers who put models into production and keep them working, not notebooks that never ship.
LLM & RAG Engineers
Engineers who build retrieval-augmented systems that answer from your own data and admit when they cannot.
Data Engineers
Engineers who build the pipelines and schemas everything else depends on, and keep them trustworthy.
MLOps Engineers
Engineers who make model delivery boring — versioned, reproducible, monitored and reversible.
What to look for when hiring
Ask a candidate how they would tell whether the feature is working in production. If the answer is only about model metrics rather than user outcomes, they have built demos rather than products.