Senior MLOps Engineer...

Senior Machine Learning Engineer - Computer Vision

• Paying up to £110k + 7.5% bonus + $10,000 in share (yearly)
  
• London - 1 day a week
  
• A chance to work closely with professional sport!!
  
  I am currently working with a global leader within SportsTech, who are currently expanding their AI offerings and are looking to hire Senior MLOps Engineers.
  
  Their platform captures, analyses, and delivers insights from live video to transform how sports teams perform at every level, with a strong emphasis in professional sport. If you're looking for a company that prioritises innovation, autonomy while working on some of the most exciting challenges in sports tech today then this is a great opportunity for you!
  
  About the Role
  
  You'll work on projects that scale across thousands of live events globally, developing new experiences and insights that power the future of sports. The team are all using Computer Vision so an understanding of how this works is beneficial but not essential.
  
  In this role, you will:
  
  
• Deliver at scale: deploy ML models across cloud and edge platforms, scaling to thousands of simultaneous matches.
  
• Lead impactful projects: Own and drive initiatives that directly enhance the experience for athletes, coaches, and fans.
  
• Collaborate cross-functionally: Work closely with engineering, product, and leadership teams to deliver best-in-class solutions.
  
  Technical requirements:
  
  
• Strong technical skills: Deep experience with Python and/or C++, plus proficiency with Kubernetes, TensorRT, Nvidia DeepStream, Nvidia Jetson, and AWS.
  
• MLOps.
  
• Product-minded approach: Demonstrated success delivering AI/ML products in collaboration with cross-functional product teams.
  
• Scalable systems expertise: Solid track record building and managing AI/ML systems in production environments at scale.
  
  Nice to Have:
  
  
• Sports tech experience: Background applying AI/ML in the sports domain for data generation or insights.
  
• Systems optimisation: Knowledge of GPU kernel development (CUDA, OpenCL, etc.), real-time system optimisation (e.g., Nvidia NSight), or experience working with embedded SoCs (Nvidia, Qualcomm, etc.).
  
  If you're interested in this role and feel you fit some of the requirements, then apply through the AD to find out more...
  
  Senior Machine Learning Engineer - Computer Vision