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."
• 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