Hire developers · AI & Cloud
AI & Cloud
Hire Machine learning engineers
Models built against a metric that matters, and the evaluation harness that says whether the next version is actually better.
What they are hired to build
The work, before the CV.
A role written against the work gets a better shortlist than a role written against a stack. These are what Machine learning engineer engineers are usually brought in to do.
Roles we recruit: Machine learning engineer · Senior machine learning engineer · Applied scientist · Data scientist (engineering-leaning).
- Prediction and scoring models with a real business metric attached
- Recommendation, ranking and forecasting features
- Evaluation harnesses and offline-to-online metric alignment
- Taking a notebook prototype to something that serves traffic
The technical screen
What the conversation actually covers.
Every candidate has a real technical conversation with an engineer who has done the job, and you get written evidence per competency. In Machine learning engineer, that conversation covers the following.
Usually assessed alongside: Python, PyTorch, scikit-learn, SQL, Pandas.
- Framing: what the label is, and why that is the right target
- Leakage — where it comes from, and how they caught it last time
- Evaluation beyond accuracy: base rates, class imbalance, cost of error
- What they would ship, and what they would refuse to ship
Three ways to bring one on
The route changes; the screening does not.
The same three routes apply whichever stack you are hiring for. Which one fits depends on how long you need the person and whether the headcount is approved.
Permanent placement
Companies hiring engineering and data roles
One fee on joining, with a 90-day replacement guarantee.
- Typical timeline
- 3–8 weeks to offer
Contract staffing & staff augmentation
Companies with budget but no headcount
We employ them, you direct them. Monthly, for when the need is real but headcount is not approved.
- Typical timeline
- Monthly, 3-month minimum
Contract to hire
Companies hiring into a new or unclear role
Three to six months as a contractor, then convert. The honest option when neither side is sure.
- Typical timeline
- 3–6 months to conversion
Or have us build it instead
If the need is the work, not the headcount.
AI & Data
AI readiness assessment
What is worth automating, what it costs at real volume, and the two things that will block you.
AI & Data
MLOps / LLMOps platform setup
Getting models into production properly, and keeping them there.
AI & Data
Data platform engineering
Warehouse, pipelines and data quality — the foundation most AI projects discover they are missing.