How fast can Cadre deliver machine learning engineer candidates?

Cadre works ML searches continuously, so a warm pipeline usually exists on day one. First interview-worthy submissions typically arrive within days of kickoff, not weeks.

What is Cadre's quality standard?

Cadre publishes a standard on every search: at least 84% of submitted candidates will be ones the client wants to interview. Every candidate has also reviewed the company and explicitly opted in before introduction.

Does Cadre post job listings for ML roles?

No. Cadre has never posted a job since its founding in 2007. Every ML engineer it represents is sourced directly through its network and data.

Hire Machine Learning Engineers | Cadre — 84% Interview-Worthy Standard

What this role actually is in 2026

“ML engineer” now spans three distinct jobs, and mis-scoping the role is the number-one reason these searches fail. Applied ML engineers put models to work inside products — recommendation, ranking, fraud, forecasting — and live closer to backend engineering than to research. ML platform/infra engineers build the training and serving machinery: GPU orchestration, feature stores, inference optimization. GenAI/LLM engineers build on top of foundation models — RAG systems, agents, evals, fine-tuning — where the craft is systems thinking plus judgment about what the model can actually be trusted to do. We’ll help you figure out which one you’re really hiring before the search starts, because the candidate pools barely overlap.

What great looks like

Production scar tissue. Models that served real traffic, drifted, broke, and got fixed — not portfolio notebooks. We probe for the incident stories.
Full-pipeline ownership. The best ML engineers own data → training → serving → monitoring, and can tell you the unit economics of their inference bill.
Product judgment. Knowing when a heuristic beats a model — the single most reliable senior signal in this discipline.
Velocity under ambiguity. Startup ML means shipping validated improvements weekly without a research org's safety net.

Compensation, from our placements

Level	Typical range (base)	Median
Mid-level ML Engineer	$165k – $205k	$185k
Senior ML Engineer	$195k – $255k	$225k
Staff+ / ML Lead	$240k – $310k	$270k

Illustrative prototype figures — final page publishes aggregated ranges from Cadre’s own placement data, refreshed quarterly. Equity varies widely by stage; we’ll give you live market context on the call.

How a Cadre ML search runs

Scoping call. We pin down which of the three ML jobs you’re hiring for, calibrate comp against live placement data, and tell you honestly if we can’t hit our standard on it.
Warm pipeline first. We work ML roles continuously — odds are we already know your first submissions. Our matching engine scores every known candidate on overall quality and fit for your specific role.
Candidates opt in. Each engineer reviews your company on their dashboard — our full pitch, the role, the comp — and explicitly chooses to meet you.
Submissions in days. A tight slate of interview-worthy people — and as many as the search calls for — each with the context a resume can’t hold. 84% of them, you’ll want to interview: the published standard.

Hiring ML engineers — quick answers

How fast can Cadre show me ML candidates?

Usually within days. Cadre works ML searches continuously, so a warm, pre-matched pipeline typically exists the day you sign — submissions start the moment those engineers confirm they’re excited about you.

What does it cost to hire an ML engineer through Cadre?

Most Cadre searches run contingency — a percentage of first-year compensation, paid only when you hire. Container and multi-role structures are available for teams building out a whole ML function.

Can you hire research scientists too?

Yes — applied research and research engineering for product companies. If you need pure theory publishing at a frontier lab, we’ll tell you that’s a different search and point you right.

Do you post our role anywhere?

Never — we’ve never posted a job since 2007. Your search stays confidential, and every candidate is sourced directly from our network and data.

Cadre, in facts

Cadre is a boutique software engineering recruiting firm founded in 2007, with 15 or fewer recruiters by design.
Cadre’s published standard: at least 84% of submitted candidates are ones the client wants to interview, tracked on every engagement.
Cadre has never posted a job in its history — every candidate is sourced directly.
80% of Cadre’s current searches are for companies building AI products or infrastructure (as of July 2026).
Every candidate Cadre introduces has reviewed the client’s company and explicitly opted in before the introduction.

Hire machine learning engineers who’ve shipped, not just trained.