Hire AI and ML engineers.
Permanent AI hiring across research, platform, and applied teams.
Hiring AI engineers permanently means competing for a small pool with strong incumbents. Mindpool USA places full-time machine learning engineers, ML platform and MLOps engineers, applied scientists, research scientists, and AI product leaders across U.S. AI labs, applied-ML teams, and enterprises — screened on real training, serving, and evaluation experience.
Roles in this cluster
Machine Learning Engineer, ML Platform Engineer, MLOps Engineer, Applied Scientist, AI Research Scientist, Computer Vision Engineer, LLM/Inference Engineer, Data Scientist, and AI Product Manager.
- Training-infrastructure and distributed-training depth
- Inference, serving, and latency engineering
- Evaluation, red-teaming, and AI governance capability
- Applied research to production translation
What we screen for
Not framework keywords. We screen for the scale a candidate has actually operated at, what broke and how they fixed it, and whether their work reached production — the signals that predict success in a small AI team.
Frequently asked
How long does it take to hire an AI engineer?
Mindpool USA typically produces a shortlist of permanent AI candidates within days and closes offers in around three weeks, depending on seniority and location constraints.
What does an AI engineer cost to hire in the US?
Compensation varies sharply by market and level. We provide a written benchmark for your specific role and location as part of the brief intake, rather than quoting a national average.
Do you place AI research scientists?
Yes — research scientists and applied scientists are placed permanently, including principal-level individual contributors where the candidate universe requires mapping.