Principal Computer Vision Engineer, Catapult Sports

• 8+ years of software engineering experience, with significant depth in at least one of: computer vision, real-time systems, ML/AI deployment, or robotics perception
• Strong proficiency in Python and C/C++ – you're comfortable across the full stack from model training to performance-critical native code
• Demonstrated experience shipping ML or CV systems to production, especially on resource-constrained or embedded platforms
• The ability to own ambiguous problems end-to-end: scoping, prototyping, shipping, and measuring
• Comfort with leadership: you've mentored engineers, led technical direction, or driven cross-team initiatives, even if your title didn't say "lead."
• Research shows that while men apply for jobs when they meet an average of 60% of the criteria, women and other marginalized groups tend only to apply when they check every box. So if you have what it takes, but don't meet every single point in our job ad, please still get in touch!

Desirable

• We are looking for a Principal Computer Vision & Tracking Engineer to own and drive the computer vision and real-time tracking systems at the heart of our camera-based products
• Based in Boston (hybrid), you will lead a small team building the perception stack that turns vision data into athlete performance insights – from neural network inference on edge AI accelerators, to 3D object tracking, to the data science that validates and extends what our system can measure. Today, that means tracking barbell-based weightlifting with sub-rep precision; tomorrow it means general human movement
• This is a role for someone who thrives on breadth. In any given week, you might be optimizing a model for edge inference, designing a new movement analysis algorithm, or analyzing data to produce athlete profiles. You'll report to a Senior Director of Engineering and player-coach a small pod of engineers while collaborating closely with our embedded platform and applications teams
• If you've built real-time perception systems that had to work reliably in the real world – on real hardware, with real constraints – this is your kind of problem
• Own the technical direction of our computer vision and tracking domain: the full pipeline from sensor readings through computer vision, motion recognition, and metric calculation
• Lead and mentor a small team (1–2 engineers), setting priorities, reviewing designs, and driving execution while remaining deeply hands-on
• Train, optimize, and deploy neural networks for real-time segmentation and classification on embedded hardware, including model conversion and optimization for edge accelerators
• Extend our tracking and motion recognition pipeline to support new movements and types of analysis
• Own the reliability of the domain: analyze tracking accuracy, build quality metrics, and use data to drive improvements across the pipeline
• In 6 months time… You have shipped at least one meaningful improvement to detection or tracking quality, and you have a deep understanding of the tracking system and how we might extend it
• In 12 months time… You've driven the roadmap for expanding our vision system to new movement types. The team is running well, and you're the go-to person across the company for anything related to how our camera system sees and understands athletes

• All offers of employment are subject to Catapult's positive prehire check