Senior/Lead ML Applied Scientist

Intuition Machines is growing rapidly. We are looking for systems, security, and machine learning engineers. If you are interested in working on cutting-edge research that rapidly goes into production at scale, this is the right place: our products serve hundreds of millions of people.

• 5+ years of professional experience in applied machine learning.
• Proven experience with the entire modeling lifecycle: building, evaluating, and debugging large ML models.
• Experience with large-scale categorical and structured data.
• Expertise in real-time ML models, incremental learning, and online learning.
• Strong understanding of ML fundamentals including bias-variance tradeoffs, loss functions, and evaluation metrics.
• Bachelor’s degree in a technical field or equivalent practical experience.
• Thoughtful, self-directed individual comfortable making independent technical decisions.

Nice to have:

• Strong grasp of math required for ML (linear algebra, probability theory, statistics, matrix calculus).
• Software engineering/development experience with large-scale distributed systems.
• Ability to collaborate with ML engineers to integrate work into infrastructure, including automating observability, deployment, quality, and security.

• Build ML models that can scale to millions of requests per second while maintaining performance.
• Translate business requirements into technical specifications.
• Develop ML models that satisfy memory and compute constraints, evaluate them properly, and debug effectively.
• Provide technical mentorship to other ML research engineers.
• Iterate quickly, focusing on shipping products or features to millions of users.
• Write clearly structured, maintainable, well-documented, and tested code, including unit, integration, and end-to-end tests.
• Participate in code reviews and architecture & design sessions.
• Stay updated on recent technological developments and assess their applicability.
• Provide technical input to the research roadmap.

All positions require pre-employment screening, including third-party verification of work history, education, identity, and a final in-person interview and identity verification in the candidate's country of residence.