ML Applied Scientist

intuition machines • Italy
Remote
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AI Summary

Design, implement, and scale machine learning systems for enterprise security products. Translate business goals into technical specifications and ensure models perform efficiently. Collaborate with teams to develop and deploy ML models.

Key Highlights
Build ML models for enterprise security products
Translate business goals into technical specifications
Collaborate with teams to develop and deploy ML models
Key Responsibilities
Build ML models that can scale to millions of requests per second while maintaining performance
Translate business requirements into technical specifications
Provide technical mentorship to other ML research engineers
Iterate quickly, with a focus on shipping early and often
Write clearly structured, maintainable, well-documented, and tested code
Technical Skills Required
Machine Learning Artificial Intelligence Python Large-scale categorical and structured data Real-time ML models Incremental learning Online learning Linear algebra Probability theory Statistics Matrix calculus
Benefits & Perks
Fully remote position with flexible working hours
Pleasant, modern development and deployment workflows
High impact: lots of users, happy customers, high growth, and cutting edge R&D
Nice to Have
Strong grasp of the math required for ML (linear algebra, probability theory, statistics, matrix calculus)
Software engineering/development experience with large-scale distributed systems

Job Description


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.

What you will do:

  • 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, with a focus on shipping early and often, ensuring that new products or features can be deployed 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

What we are looking for:

  • 5+ years of professional experience in applied ML
  • 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: bias-variance tradeoffs, loss functions, evaluation metrics, etc
  • Bachelor's degree in a technical field (or equivalent practical experience)
  • Thoughtful, self-directed individual who is comfortable making technical decisions independently

Nice to Have:

  • Strong grasp of the 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 your work into our infrastructure, including automating observability, deployment, quality, and security

What we offer:

  • Fully remote position with flexible working hours
  • An inspiring team of colleagues spread all over the world
  • Pleasant, modern development and deployment workflows: ship early, ship often
  • High impact: lots of users, happy customers, high growth, and cutting edge R&D
  • Flat organization, direct interaction with customer teams

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.

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