Hire Machine Learning Engineers

Specialist ML engineer recruitment for US startups

Find ML engineers who can take models from experiment to production — screened for technical depth and startup fit.

ML Engineer Recruitment From People Who Understand the Role

“Machine learning engineer” covers a wide range of people. Some are closer to researchers, some to data engineers, and some to backend engineers who deploy models. Hiring the wrong profile is one of the most common and expensive mistakes a startup can make in AI.

We start by working out which ML engineer you actually need for your product and stage. Then we headhunt for that profile — including the many strong engineers who are not actively applying for jobs.

Applied ML Engineers

Build, train and ship models that solve a specific product problem, from ranking and recommendations to forecasting and classification.

ML Platform & MLOps Engineers

Build the pipelines, feature stores, deployment and monitoring that let your team ship models reliably.

Computer Vision Engineers

Engineers experienced with image and video models, from data pipelines to on-device or cloud inference.

NLP & LLM Engineers

Engineers who work with language models, retrieval and evaluation to build language-driven product features.

Data Scientists

Scientists who design experiments, build models and turn analysis into product decisions.

ML Leads & Heads of ML

Technical leaders who can set your ML strategy, own delivery and grow the team behind it.

What We Screen For

Every candidate we put forward has been assessed against what your role needs, not just a list of frameworks. Depending on the role, that typically includes:

Production experience. Models that have been deployed, monitored and maintained, not only trained.
Engineering fundamentals. Clean code, testing, version control and working within a wider engineering team.
Data judgement. An understanding of data quality, leakage and evaluation, and when a simpler approach will do.
Domain and stack fit. Experience with the problem types, tools and cloud platforms you use, or a clear ability to learn them.
Startup fit. Comfort with ambiguity, ownership and moving quickly with limited resources.

Hiring Your First Machine Learning Engineer

Your first ML hire is different from hiring into an established team. They will make early decisions about data, tooling and infrastructure that your company lives with for years, often without a senior ML colleague to learn from. We help you decide whether you need a hands-on generalist, a specialist or a leader, set a realistic level and compensation, and find people who have built from scratch before.

If this is your first AI hire, see our founding AI engineer search.

How the Process Works

We agree the role and the pitch with you, run a targeted search, screen candidates for technical depth and fit, and manage interviews through to offer and acceptance. You get regular updates and honest market feedback on compensation, location and expectations throughout.

We recruit ML engineers on a permanent or contract basis, and for on-site, hybrid and remote roles. Need a broader team? Read about our AI staffing for startups or how we help you hire LLM and generative AI engineers.

Frequently Asked Questions

Looking for ML Engineers?

Tell us about the role and your product, and we’ll share an honest view of the market and how we’d approach the search.