Lead ML Engineer

Job Overview

We are looking for a Lead Machine Learning Engineer with strong software engineering skills and a creative mindset for ML-focused problem-solving. You will lead large-scale ML projects and products from inception to production, overseeing the entire lifecycle from design and implementation to deployment and maintenance.

Key Responsibilities

• Lead large-scale ML projects and products from inception to production
• Make key architectural decisions to ensure solutions are scalable, efficient, and maintainable
• Drive collaboration across ML and engineering teams to ensure product success
• Design and implement state-of-the-art machine learning pipelines and models
• Set technical standards and lead the development of scalable, testable, and high-performance applications
• Provide leadership and mentorship to other ML engineers

Required Qualifications

• 7+ years of experience building and maintaining large-scale production ML systems
• Proven experience as the owner or significant contributor to products used by tens of thousands of customers
• Expertise in machine learning algorithms, productionizing ML models, and scaling systems
• Strong problem-solving skills with creative approaches to overcoming technical challenges
• Experience leading technical discussions and setting technical standards for a team
• Excellent written and verbal communication skills
• Familiarity with modern orchestration platforms (Kubernetes, containerization, microservice design)

About Intuition Machines

Intuition Machines builds enterprise security products with an AI/ML focus. We apply our research to systems that serve hundreds of millions of people, with a team distributed around the world. Our best-known product is the hCaptcha security suite. Our approach is simple: low overhead, small teams, and rapid iteration.

Benefits

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