Lead ML Engineer

Intuition Machines, Inc.; United States; Remote; USD 160,000 - 260,000; Full time

Benefits offered by this job

Fully remote

Job summary

Intuition Machines, Inc. is seeking a Lead Machine Learning Engineer with strong software engineering skills to drive ML products from concept to production. You will own end-to-end design, implementation, deployment, and maintenance.

Lead cross-functional teams, set technical standards, and design scalable ML pipelines. You will mentor engineers and shape the technical strategy, delivering high-impact solutions for millions of users in a fully remote environment.

Qualifications

• 7+ years of experience building and maintaining large-scale production ML systems.
• Owner or significant contributor to products used by tens of thousands of customers, with the ability to make complex design decisions.
• Expertise in machine learning algorithms, productionizing ML models, and scaling systems to handle large data volumes.
• Strong problem-solving skills with creative approaches to overcoming technical challenges.
• Experience leading technical discussions, driving decisions, and setting technical standards for a team.
• Excellent written and verbal communication skills, with the ability to articulate complex technical topics to both technical and non-technical stakeholders.

Responsibilities

• Lead large-scale ML projects from inception to production, overseeing the lifecycle from design to deployment and maintenance.
• Make key architectural decisions to ensure scalable, efficient, and maintainable solutions.
• Drive collaboration across ML and engineering teams to ensure product success and influence technical discussions.
• Design and implement state-of-the-art ML pipelines and models impacting millions of users.
• Set technical standards and lead development of scalable, testable, high-performance applications.
• Provide leadership and mentorship to other ML engineers, fostering growth of the ML engineering organization.

Skills

ML engineering

Distributed systems

Kubernetes

Containerization

Microservice design

Production ML

Leadership

Code review

Tools

Kubernetes

Docker

CI/CD

Job description

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. You are probably familiar with our best-known product, the hCaptcha security suite. Our approach is simple: low overhead, small teams, and rapid iteration.

We’re looking for a Lead Machine Learning Engineer with strong software engineering skills and a creative mindset for ML-focused problem-solving.

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 here:

• Lead large-scale ML projects and products from inception to production, overseeing the entire lifecycle from design and implementation to deployment and maintenance.
• Make key architectural decisions to ensure solutions are scalable, efficient, and maintainable while balancing business and technical constraints.
• Drive collaboration across ML and engineering teams to ensure product success, influencing technical discussions and decisions at all levels.
• Design and implement state-of-the-art machine learning pipelines and models that impact millions of users and generate real business value.
• Set technical standards and lead the development of scalable, testable, and high-performance applications.
• Provide leadership and mentorship to other ML engineers, fostering the growth of a strong Machine Learning Engineering organization.

What you will learn:

• Work on systems that affect millions of users daily, scaling machine learning systems with billions of data points and millions of inferences per second.
• Gain experience in architecting and scaling advanced ML solutions for real-world challenges, moving beyond standard approaches from research papers.
• Have the opportunity to define technical strategy, contribute to significant ML advancements, and guide the future direction of ML systems at scale.

What we are looking for:

• 7+ years of experience building and maintaining large-scale production ML systems, with a focus on performance, scalability, and reliability.
• Proven experience as the owner or significant contributor to products used by tens of thousands of customers, with the ability to make complex design decisions.
• Expertise in machine learning algorithms, productionizing ML models, and scaling systems to handle large data volumes.
• Strong problem-solving skills with creative approaches to overcoming technical challenges.
• Experience leading technical discussions, driving decisions, and setting technical standards for a team.
• Excellent written and verbal communication skills, with the ability to articulate complex technical topics to both technical and non-technical stakeholders.
• Familiarity with modern orchestration platforms (Kubernetes, containerization, microservice design) and distributed systems.
• Ability to identify, define, and segment complex research problems and drive innovative solutions that align with business and technical goals.

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.