Machine Learning Manager, Security & Research

Intuition Machines, Inc.
8hRemote

About The Position

Intuition Machines security products are used at scale by category leaders in every industry. You are probably familiar with our best-known product, the hCaptcha security suite. Our approach is simple: high agency, small teams, and rapid iteration. AI/ML is at the core of our products. We build our systems for speed, with a team distributed around the world. As an Engineering Manager you will lead our ML Security team as we build security products including bot, agent, and human fraud and abuse detection. You will execute roadmaps, iterate on current and new products, and drive team growth while working with research, product, and tech leads. Engineering Manager roles are hands on and highly technical here: while you won't be coding every day, you are expected to review code/PRs, act as a tech lead when required, and mentor engineers in your areas of expertise.

Requirements

  • Strong ML/data science or engineering background with production ML experience.
  • Engineering management and/or tech lead experience with ability to engage engineers and researchers on technical topics.
  • Expertise in high-availability systems, Python, ML pipelines, and distributed systems.
  • Experience with MLOps, ML systems, and large-scale internet-facing applications.
  • Strong communication skills across technical and non-technical audiences.
  • Ability to prioritize and coordinate engineering team work.

Responsibilities

  • Lead ML Security team execution and delivery, collaborating with cross-functional partners.
  • Make architectural and technical decisions, staying hands-on with code reviews and design.
  • Mentor team members, ensuring their growth and engagement.
  • Build ML solutions from data exploration through production deployment and monitoring.

Benefits

  • 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.
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