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Intuition Machines, Inc. is seeking an ML Applied Scientist to design, implement, and scale machine learning systems powering our products.
You will translate business goals into technical specifications and ensure models perform under real-world constraints in a fast-paced production environment. You will work across teams to scale ML models for millions of requests per second, provide mentorship to ML engineers, and contribute to the research roadmap while shipping reliable, well-tested code.
Intuition Machines uses AI/ML to build enterprise security products. We apply our research to systems that serve hundreds of millions of people, with a team distributed around the world. You are probably familiar with our best-known product, the hCaptcha security suite. Our approach is simple: low overhead, small teams, and rapid iteration.
As an ML Applied Scientist, you will design, implement, and scale machine learning systems that power our products. You’ll work across teams to translate business goals into technical specifications, ensuring our models perform efficiently under real-world constraints. This role combines research, engineering, and mentorship in a fast-paced production environment.
Using AI: Coding agents are indisputably useful tools. We provide access to the top 3 models, and were early adopters of evals-first development flows. Familiarity with coding using agents is part of all interviews. However, reliability and correctness are critical for us. You will need to read and understand every line of code with your name on it, and it will be reviewed by both people and machines.
What you will do:
What we offer:
We celebrate equality of opportunity and are committed to creating an inclusive environment for all team members.
Join us as we transform cybersecurity, user privacy, and machine learning online!
Please note that all positions require pre-employment screening, including third-party verification of work history, education, and identity, as well as a final in-person interview and identity verification step, which will be conducted in your country of residence.