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For AI & ML engineers
If you build AI systems, we'd like to know you — whether or not you're looking. Confidential conversations, an honest read on the market, and only roles that fit.
- Confidential
- Roles that fit
- Honest market reads
Why talk to us
Most people we place weren't looking
Careers in this market move on their own rhythm.
You join a company for a specific problem, you see it through, and the right moment to move arrives once every couple of years. The recruiters worth talking to are the ones who've been in touch long before it does.
We work only in AI and machine learning engineering, so the conversation starts where you are: what you built, what broke, and what you'd want to work on next. We'll tell you honestly where you sit in the market and which companies are worth your time.
What you can expect
How we work with engineers
01
An honest read on the market
What you're worth, who's hiring, which companies are genuinely well funded and which are running on a story. If a role you're considering looks like a mistake, we'll say so.
02
Only roles that fit
We won't send you roles that don't fit. If we get in touch, it's because the specific problem looks interesting for you — not because your title matched a keyword.
03
Confidentiality
Nothing goes anywhere without your explicit agreement, every time. No resume sent speculatively, no name mentioned to a company you haven't approved.
04
A real technical conversation
We'll ask what you built, what broke and what you'd do differently, because that's what we'll be representing. You won't be asked to explain what RAG stands for.
05
Guides worth reading
Our hiring guides are written for the companies interviewing you. Knowing what they're being told to screen for is useful from your side of the table too.
06
A long-term relationship
If the timing isn't right, we keep in touch. The right move often comes well after the first conversation, and we'd rather be there for it than push you into the wrong one.
HireAIEngineers.com · For engineers
The best move is rarely the one you went looking for
What we recruit
Across the AI stack
From the product layer to the GPUs underneath it, and from first engineer to CTO.
01
AI engineering
LLM applications, agents and tool use, orchestration, RAG and retrieval, context engineering, evaluation and quality.
02
Machine learning
Model training and fine-tuning, classical ML, recommendation and ranking, research engineering and applied science.
03
ML infrastructure
LLMOps and MLOps, GPU and training infrastructure, inference and serving, routing and caching, cost and latency engineering.
04
Data for AI
Platforms and pipelines, labeling and annotation operations, synthetic data, quality, lineage and governance.
05
Forward deployed & AI product
Customer-embedded engineering, GTM engineering, and the full-stack builders who own an AI feature end to end.
06
Leadership
Founding engineers, Heads of AI and ML, Head of ML Platform, VP Engineering, Chief AI Officer and CTO.
Roles worth moving for
The detail you need before you take a call
Strong engineers move for the problem, not the title. So when we bring you a role, we bring the things you'd want to know before giving up an evening to interview:
The technical problem, and where the system is immature today
The team you'd join, the stack, and the data you'd work with
Funding, runway and what we know about the founders
The package, including how the equity is structured
How it works
From first call to first day
About what you've built, what you'd want next, and what would actually make you move. A brief, informal call.
Where you sit in the market, what's realistic, and what would strengthen your position.
When something fits, we come to you with the problem, the team, the stack, the data, the package, and what we know about the founders.
Nothing is shared with any company without your explicit say-so.
We prepare you properly for the process, and give you real feedback afterwards either way.
If the timing isn't right yet, we keep in touch and come back when something genuinely fits.
Where the roles are
- AI-native startups and scale-ups
- Established companies building serious AI capability
- Labs, platforms and infrastructure providers
- On-site, hybrid and remote, wherever the right role is
Wayne Lindor
PRINCIPAL | PRIZED
Wayne heads up the AI Engineering practice at Prized, working with AI and ML engineers across LLM applications, agents, evaluation, machine learning, research and ML infrastructure.
Hiring senior leaders into one of the fastest-growing consultancies in the world gave him a deep appreciation of both sides of the desk — and a firm belief that candidate experience is paramount. If you'd like an honest read on the market, get in touch.
Let's talk
Tell us what you work on and what you'd want next. Nothing is shared with any company without your agreement.