Staff ML Engineer (Ops, Vision)
We're building the next generation of real-time sports analytics, processing millions of games annually through advanced computer vision systems. Our platform serves as the backbone for teams ranging from high school to professional leagues, requiring robust ML infrastructure that operates at scale across edge devices and cloud systems.
As the technology arm of a leading sports analytics company, we've established ourselves as the primary provider for over 200,000 teams globally. Our infrastructure processes over 3 million games yearly, requiring sophisticated ML pipelines and real-time video processing capabilities that push the boundaries of current computer vision technology.
As a Staff ML Engineer, you'll lead the technical direction of our ML infrastructure, focusing on optimizing our computer vision models for real-world deployment. Your work will directly impact how teams analyze and improve their performance, requiring expertise in both theoretical ML concepts and practical system design.
What we offer:
* Competitive compensation: Up to £145k base + benefits
* Fully remote work environment with flexible hours
* Access to cutting-edge GPU infrastructure and sports datasets
* Direct collaboration with professional sports organizations
* Clear path to Senior Staff and Principal Engineer roles
* Annual conference and learning budget
Key responsibilities:
* Architect and implement ML pipelines for real-time video processing
* Optimize model inference for edge deployment using TensorRT
* Lead the design of our next-gen computer vision infrastructure
* Mentor senior engineers and shape technical direction
* Drive MLOps best practices across distributed teams
* Collaborate with research teams on model development
Keywords: TensorRT, PyTorch, CUDA, MLOps, Kubernetes, Computer Vision, Edge Computing, Real-time Processing, Distributed Systems, Model Optimization, OpenCV, Docker