Senior MLOps Engineer

We’re looking for a Senior MLOps Engineer to join our team and deliver new experiences and valuable insights to our coaches, athletes and fans. You’ll help us build and deploy game-changing initiatives that use cutting-edge computer-vision and deep learning at scale to shape the future of sports at every level, from professional teams to local high schools.

As a Senior MLOps Engineer, your priorities will include:

• Delivering for customers at scale. Optimise and deploy ML models and systems on both cloud and edge environments, scaling to thousands of simultaneous sports matches.
• Leading projects. You’ll own the work to deliver high-impact results for customers and the business, all in service of your team’s quarterly goals.
• Collaboration. By working closely with other teams and cross-functional leaders to deliver your projects in small increments, you’ll ensure our products meet the highest standards.
• Support your team. You’ll optimise your team’s ML lifecycle across optimisation, deployment and monitoring, so your team can have more impact, faster.

For this role, we’re currently considering candidates who live within a commuting distance of our office in London. But with our flexible work policy, there aren’t any current requirements for the number of days you come to the office.

• Technical expertise. You have extensive experience in C++/Python, and several of the following areas: Kubernetes, Nvidia Jetson, and AWS (or other cloud services). Experience with TensorRT and Nvidia DeepStream would also be a plus.
• A product focus. Your proven track record of delivering impactful AI/ML products with close collaboration with product is impressive.
• System experience. When it comes to building, maintaining and monitoring complex AI/ML systems in production at scale, you’re a pro.

• Sports industry experience. If you’ve used AI/ML in sports to generate data and/or create insights, that’s a plus.
• Deeper systems knowledge. Extra experience with any of the following would be an asset: developing GPU kernels and/or ML compilers (e.g. CUDA, OpenCL, TensorRT Plugins, MLIR, TVM, etc); optimizing systems to meet strict utilization and latency requirements with tools such as Nvidia NSight; and/or you’ve worked with embedded SoCs (e.g. Nvidia, Qualcomm, etc.).

• Champion work-life harmony . We’ll give you the flexibility you need in your work life (e.g., flexible vacation time above any required statutory leave, company-wide holidays and timeout (meeting-free) days, remote work options and more) so you can enjoy your personal life too.
• Guarantee autonomy . We have an open, honest culture and we trust our people from day one. Your team will support you, but you’ll own your work and have the agency to try new ideas.
• Encourage career growth. We’re lifelong learners who encourage professional development. We’ll give you tons of resources and opportunities to keep growing.
• Provide an environment to help you succeed . We’ve invested in our offices, designing incredible spaces with our employees in mind. But whether you’re at the office or working remotely, we’ll provide you the tech you need to do your best work.
• Support your wellbeing. Depending on location, we offer medical and retirement benefits for employees—but no matter where you’re located, we have resources like our Employee Assistance Program and employee resource groups to support your mental health.

Hudl is an equal opportunity employer. Through our actions, behaviors and attitude, we’ll create an environment where everyone, no matter their differences, feels like they belong.

We offer resources to ensure our employees feel safe bringing their authentic selves to work, including employee resource groups and communities. We track our efforts in annual inclusion reports.

Please don’t hesitate to apply—we’d love to hear from you.

Hudl is committed to protecting personal data and providing information about how we collect and use it in our recruitment process. Hudl acts as data controller and may transfer data as described in our notices. Diversity information is collected on a voluntary basis and will be kept confidential and separated from your application during review.