Ranking, fraud, forecasting and vision models
Machine Learning Engineer Recruiters for AI Startups in NYC
Our machine learning searches for New York City AI startups start with two questions: what data you have, and which part of the model work your new hire will own. Then we look for engineers whose models already run in production.
At a glance
Which machine learning hire do you need?
An applied scientist, an MLOps engineer and an ML platform engineer solve different problems. We pin down which one your roadmap needs first.
Roles we recruit for
ML engineers, applied scientists, MLOps and ML platform engineers
Stages
Seed to Series C
Where
New York City. In office, hybrid or remote
Who we look for
Engineers whose models run in production and moved a number the business tracks
Speed
Our last 3 hires averaged 17 days
How you pay
Retained, success-based or embedded. Terms agreed upfront
How we assess
ML engineers whose models made it to production
The first thing we ask an ML candidate is which of their models is serving traffic today. The rest of our assessment builds on that answer.
01
Got models into production
What was deployed, how often it was retrained and how much traffic it served. Notebook work alone doesn't clear this bar.
02
Moved a business number
Accuracy on a test set is a start. We ask which business number their model changed and how they proved the model caused it.
03
Owns the data
Most ML problems start in the data. The strongest candidates built or fixed their own pipelines, labels and features.
04
Keeps models healthy
We ask how they noticed a model getting worse in production, what alerted them and what they put in place so the next drop was caught sooner.
Production deployments
Business impact
Data pipeline work
Comp expectations
Modeling depth
ML system design
Production code
Who runs your search
Liam, Founder of StellarSearch
Our team brings 20+ years of search experience across engineering, AI/ML, product and GTM.
LinkedIn ↗
Client feedback
Feedback from founders and the engineers we placed
I'm not really sure how he does it, but he continues to find us top tier talent that fits exactly what we're looking for."
I'm very grateful they reached out."
Would highly recommend."
They did a great job explaining roles, companies, and interview processes and was friendly + supportive throughout."
Where our hires come from
We've placed people from teams like these
We look past titles to the work: ex-founders, early employees and people doing their best work outside the day job.
How we work
How we run your search
From the first call to an accepted offer. What we handle, and the few places we need you.
Learn what you're building, what the hire owns in the first 90 days, and the comp, equity and location you can offer.
One call with the founders.
Map the market from day one. If the problem is sourcing, pay, location, process or the profile, we tell you early.
Agree any changes to the brief.
Approach people who aren't applying anywhere, and assess each one on evidence before they reach you.
Nothing. This part is ours.
Send each candidate with our write-up, then schedule and keep the process moving.
Run your interviews.
Advise on the offer, handle the back and forth, and close.
Make the final call.
If the search isn't working, we tell you fast. We use market data to recalibrate instead of sending weaker candidates for weeks.
Ways to work with us
Three ways to work with us
Pick the model that fits the hire. All terms are agreed upfront, with no hidden fees.
Best for a priority hire
Retained
A dedicated search for the one hire that can't wait. We commit time to your role from day one.
Dedicated search from the first call
Market map shared with you
Fee agreed upfront
Best for a single hire
Success-based
We run the search and you pay when the hire is made.
No fee until you hire
Same assessment on every candidate
Terms agreed before we start
Best for several roles
Embedded
We work as part of your team across several hires, for a monthly fee plus a reduced success fee.
Monthly fee plus reduced success fee
One hiring standard across roles
Works alongside your in-house team
Start a search
Describe the ML work you need covered
Tell us what you're building. We'll come back with how we'd run the search.
Looking for a role? See open jobs
Do we need a machine learning engineer or a data scientist?
ML engineer or MLOps engineer: which comes first?
Should we require a PhD for machine learning engineers?
Do we need an ML engineer if we build on hosted LLMs?
Can we hire ML engineers from New York's quant and trading firms?
How much does industry experience matter for an ML engineer?
How quickly will we see candidates?
We already have an in-house recruiter. Why use you?
How much of the process do you own?
What if the search isn't working?
How do you charge?
Hiring your founding team?
Tell us what you're building. We'll find the experts who can build and ship it.
Start Hiring
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