The ad says“Excellent communication and cross-functional partnership skills: you can align engineers, technical leads, and leadership”
The ad says“2-5+ years of engineering management experience leading machine learning engineering teams in production, with strong technical depth and experience in machine learning, computer vision (detection/segmentation), multimodal image+text models, and/or data engineering before that”
The ad says“Excellent communication and cross-functional partnership skills: you can align engineers, technical leads, and leadership”
The ad says“2-5+ years of engineering management experience leading machine learning engineering teams in production, with strong technical depth and experience in machine learning, computer vision (detection/segmentation), multimodal image+text models, and/or data engineering before that”
The ad says“2-5+ years of engineering management experience leading machine learning engineering teams in production, with strong technical depth and experience in machine learning, computer vision (detection/segmentation), multimodal image+text models, and/or data engineering before that”
The ad says“2-5+ years of engineering management experience leading machine learning engineering teams in production, with strong technical depth and experience in machine learning, computer vision (detection/segmentation), multimodal image+text models, and/or data engineering before that”
The ad says“Experience mentoring engineers to grow into broader technical leadership roles”
The ad says“2-5+ years of engineering management experience leading machine learning engineering teams in production, with strong technical depth and experience in machine learning, computer vision (detection/segmentation), multimodal image+text models, and/or data engineering before that”
The ad says“Strong judgment on organizational design: how to structure a team, allocate headcount across projects, and balance depth vs. breadth as the stack grows”
The ad says“Production deployment ownership: you’ve shipped models to production and been responsible for endpoint and model health”
The ad says“2-5+ years of engineering management experience leading machine learning engineering teams in production, with strong technical depth and experience in machine learning, computer vision (detection/segmentation), multimodal image+text models, and/or data engineering before that”
Values
The ad says“Heavy interest in manufacturing: you either have past exposure to it or are excited to learn as much about it as possible from experts here and help others do the same. This is core to our culture”
Technical Data Intelligence has the mission of making the world’s engineering data legible to automation. Ingesting high variance engineering design data in the form of engineering drawings and CAD models is crucial to assess part and assembly manufacturability, plan build processes, plan factories, and drive manufacturing process automation. This team includes both machine learning engineers and fullstack software engineers
You will build and manage a team of engineers focused on solving this problem. The solutions will be mix of agent development, classical ML development, and systems for tracking, editing, and mutating this data. This is a people-first management role: your focus is on hiring, growing, and supporting a world class team, while staying close to the technical work to help guide direction and staffing decisions, jumping in when necessary to unblock the critical path or understand the problems and technology on a deeper level
Own the people leadership of your engineers: hiring, onboarding, mentorship, career growth, and performance
Stay technically hands-on as a player-coach: participate in design reviews and contribute directly to the work when it helps the team move faster or clears a critical path
Set technical direction and where we invest headcount, in partnership with the engineers and technical leads who drive architecture and modeling decisions
Build and maintain annotation tooling, implement active learning loops, and engineer synthetic data augmentation strategies
Ensure engineers are engaged, growing, and set up to do their best work
Benefits
100% coverage of platinum medical, dental, vision, and life insurance plans for employees 401k
Relocation stipend if you’re moving from outside of LA
Flexible vacation policy
Preferred experience
Production deployment ownership: you’ve shipped models to production and been responsible for endpoint and model health
Strong judgment on organizational design: how to structure a team, allocate headcount across projects, and balance depth vs. breadth as the stack grows
Heavy interest in manufacturing: you either have past exposure to it or are excited to learn as much about it as possible from experts here and help others do the same. This is core to our culture
A track record of running a healthy team: clear expectations, direct feedback, and a strong sense of ownership among your engineers
2-5+ years of engineering management experience leading machine learning engineering teams in production, with strong technical depth and experience in machine learning, computer vision (detection/segmentation), multimodal image+text models, and/or data engineering before that
Excellent communication and cross-functional partnership skills: you can align engineers, technical leads, and leadership
Strong sense of connecting technical work and product development to business outcomes to understand what matters and what to say no to
A track record of scaling a team through a period of fast headcount growth
Experience mentoring engineers to grow into broader technical leadership roles