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Principal Computer Vision Engineer
- Boston, Massachusetts, United States
- Boston, Massachusetts, United States
Über
We work with over 5,000+ teams around the world, empowering coaches, managers and trainers in premier teams in the NFL, NBA, NHL, MLS, EPL, AFL, NRL, NCAA and more. We provide the information they need to optimize athletes’ health, game-day readiness, and performance, as well as in-game tactics.
Catapult is a sports technology company that empowers professional teams to make data-driven decisions. We deliver health, performance, video, and AI insights from the locker room to competitive environments, ensuring every decision is an opportunity to gain an advantage, sharpen performance, and build lasting success.
WE WANT PEOPLE WHO ARE PASSIONATE ABOUT SOLVING HARD PROBLEMS 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.
WHAT YOU’LL DO
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.
WHAT YOU’LL NEED
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.”
Nice to have – and what would make you exceptional:
Deeper knowledge of the mathematics behind tracking systems: 3D geometry, camera models, state estimation, filtering, optimization.
Experience with edge AI accelerators and inference optimization libraries.
Background in pose estimation, human movement analysis, or biomechanics.
Experience with depth cameras (structured light, time‑of‑flight) and 3D perception.
Familiarity with embedded Linux, Docker on ARM, and systems‑level debugging.
WHAT YOUR SUCCESS WILL LOOK LIKE
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.
WHY CATAPULT?
We have amazing people. We promise you’ll work with some of the most ambitious, intelligent people in an exciting industry, and do some of the best work of your life.
We encourage our people to engage in constructive, open, and honest communication to make Catapult extraordinary.
We work in a collaborative yet challenging environment to consistently improve our performance, which in turn impacts our customers’ performance.
Our workforce spans more than 20 countries. You’ll have the opportunity to work with people from multiple nationalities and cultures, and to build your global awareness.
We value improvement and development. We are challenging ourselves to continuously grow and become a high‑performance company. That means we maintain a growth mindset in everything we do, and our people are always looking for ways to improve. There is an unlimited opportunity to grow, do more, and do better.
Whether you’re interested in sports or not, you’ll have the satisfaction of knowing your work is supporting some of the most successful teams and athletes on the planet!
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! We would love to have a chat and see if you could be a great addition to our team. We are building the future of sports performance. Our priority is to find the brightest talent who can add to our team culture, actively contribute, and be excited about what they do.
All offers of employment are subject to Catapult’s positive prehire check. To find out more, please contact the Talent Partner for this role.
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Sprachkenntnisse
- English
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