Hiring AI infrastructure engineers
Hire AI infrastructure and ML platform engineers
MiiMate helps startups hire the engineers who make AI run well in production: ML platform engineers, inference engineers, MLOps and the people who fine-tune small models and route work between them.
More teams are sending everyday AI work to small, specialized models and keeping the largest models for the hard problems, and some are running models on their own infrastructure to keep data close and costs predictable. That takes a specific set of people, and we search for them every night.
The people who make it work
- ML platform engineersWho build serving, deployment, monitoring and the pipelines from experiment to production.
- Inference engineersWho make models fast and affordable to run, from batching and caching to model compression.
- Applied ML engineersWho fine-tune small models on your data and measure whether they're good enough.
- AI routing and gateway engineersWho decide which model handles each request, and keep quality, cost and security in check.
- Technical leadersSuch as a Head of ML Platform, from Series B onward.
How it works
Tell us what great looks like
The role, the must-haves and the team.
Otto searches every night
Including people who aren't looking.
The candidate says yes
A recruiter talks with each one, and they approve how we present them.
You decide from one link
Interested, pass or request an interview. We book it.
Every placement comes with a written replacement guarantee. More on how we work
Where we hire
New York, San Francisco, San Jose, Seattle, Boston, Austin, Chicago, Washington DC, Denver, Atlanta, Raleigh, Charlotte, Nashville, Detroit, Salt Lake City, San Antonio, Dallas-Fort Worth, Phoenix, Miami, Pittsburgh, Huntsville, AL, Columbus, OH, and remote teams across the US.
Questions founders ask us
What should our first AI infrastructure hire be?
For an early-stage team, one strong ML platform engineer who is comfortable with inference is often the right first hire. The rest can follow as your product and usage grow.
Do we need to run our own models?
Not always. It's worth it for high-volume, repeatable AI work, for customers who need their data kept close, and where speed matters. If most of your AI work is open-ended reasoning, one large model may be simpler. We're happy to talk it through before you hire.
How much does it cost?
Our fee is agreed up front in a short, plain-English agreement you accept online: a percentage of the new hire's first-year base salary or a flat fee per hire. On a contingency search you pay only when you hire someone we introduced. On a retained search, a fee is due to start the search, and the remaining terms are agreed up front. Get in touch and we'll talk through the search and the terms.
Does AI decide who we see?
No. Otto AI does the heavy searching and matching, and a recruiter on our team reviews every candidate and makes every decision about who we introduce to you.
Where do you recruit?
Across the major US tech hubs, including New York, San Francisco, Seattle, Boston, Austin and Chicago, and for remote teams anywhere in the US.