Machine Learning Engineer

• Design, train, fine-tune, and evaluate machine learning models across various domains (spanning foundational models, generative AI, computer vision, and predictive analytics) for real-time officiating and sports applications.
• Build evaluation frameworks that hold models to broadcast and officiating standards, ensuring outputs are accurate, defensible, and robust.
• Adapt state-of-the-art research into practical, production-ready solutions tailored to our unique latency and accuracy constraints.

ML Ops & Production Systems

• Own the deployment path for models: establishing CI/CD for training and inference, as well as robust model versioning and registries.
• Build and maintain data, labeling, and training pipelines with experiment tracking and reproducibility to ensure results are traceable.
• Stand up monitoring for models in production-tracking performance, drift, and data-quality signals to catch regressions before they impact live broadcasts.
• Optimize models to run efficiently under real-time latency budgets, partnering with platform engineers on scalable serving and integration.

Operational Excellence

• Design for reliability, observability, and reproducibility from day one.
• Champion sound experimental and engineering practices within a collaborative, fast-moving environment.
• Continuously explore and adopt new models, techniques, and AI-assisted workflows to raise both model quality and team velocity.

You thrive in ambiguity and bring a researcher’s rigor with a builder’s bias for shipping. You’re as comfortable fine-tuning a foundational model or improving a detection pipeline as you are building the infrastructure that trains, deploys, versions, and monitors them in production. From experimentation through live inference, you will own ML problems end-to-end and build the operational backbone that makes them dependable., * Five to ten years of engineering experience, spanning applied machine learning and the infrastructure that supports it.

• Deep proficiency in Python for model development, data processing, and production ML code.
• Hands-on experience training and deploying models in PyTorch, TensorFLow, JAX, or similar frameworks.
• Demonstrated experience taking ML models from experimentation to production, including training, evaluation, deployment, and ongoing operation.
• Experience building and maintaining production systems and data pipelines.
• Comfortable in a small team environment: collaborative, self-directed, and highly accountable.
• Strong and proactive communication; you surface technical tradeoffs, risks, and opportunities clearly.

Nice to Have

• Experience fine-tuning open-weight models for specific downstream tasks.
• Familiarity with Google Cloud Platform (GCP) and its ecosystem of data and ML tools.
• Experience building hardware-accelerated video processing and streaming pipelines using GStreamer, NVIDIA DeepStream SDK, and CUDA.
• Familiarity with model optimization and high-performance inference engines, including TensorRT, ONNX Runtime, and model compression techniques like FP16/INT8 quantization.
• Experience with real-time or low-latency inference and high-throughput data processing.
• Background in sports technology, broadcast, or other domains with hard real-time and accuracy constraints.
• Enthusiasm for sports! Bonus points if you have competitive athletic experience.
• Experience at an early-stage startup where you’ve worn many hats and shaped technical culture.

Pulled from the full job description

• 401(k) 4% Match
• Health insurance
• 401(k) matching
• Vision insurance
• Health savings account
• Dental insurance
• Unlimited paid time off, * Work on a product that is actively being used on live television by major sports leagues.
• Join a small, world-class team where your contributions are visible and your impact is real.
• Shape the technical foundation of a category-defining platform at the intersection of AI and sports.
• Competitive compensation, equity, and benefits at a well-funded, high-momentum startup.
• 100% company-paid medical, dental, and vision for you and your dependents, with an HSA contribution on the high-deductible plan.
• 401(k) with a 4% company match, plus a $200/month wellness stipend and unlimited PTO.
• A culture built by elite athletes, with high performance, high accountability, and genuine team spirit.

Compensation Range: $185K - $252K

Owl AI is the world’s first end-to-end AI platform built to bring fairness, clarity, and immersion to judged and referee-influenced sports. Founded by Olympic athlete and X Games CEO Jeremy Bloom alongside former Google Cloud AI Chief Josh Gwyther, we made history at the 2025 X Games Aspen becoming the first artificial intelligence to judge a professional sport on live broadcast television.