Your Role

We’re looking for a ML Engineer II to join our Applied Machine Learning team and deliver new experiences and valuable insights to our coaches, athletes and fans across Hudl.  You’ll drive game-changing initiatives that use cutting-edge computer vision and deep learning at scale to shape the future of sports, from professional teams to local high schools.

At Hudl, ML Engineers:

• Deliver for customers at scale. You’ll contribute to ML models and systems on both cloud and edge environments, scaling to thousands of simultaneous sports matches.
• Collaborate. You’ll work in a cross-functional team with Data Scientists and Engineers to deliver end-to-end for our customers.

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.

Must-Haves

• Technical expertise. You have hands-on experience in C++, Python, and several of the following areas: Kubernetes, PyTorch, MLOps (automated re-training, drift monitoring) TensorRT, Nvidia DeepStream/Gstreamer, and AWS.
• A proven track record. You know how to focus on products, delivering impactful AI/ML products through close collaboration with partners.
• Strong communicator. You can easily and clearly express yourself. You’re able to convey technical concepts and trade-offs to cross-functional stakeholders
• Growth mindset. You’ve picked up new technologies and domains on the job. You appreciate ambiguous work that has many possible implementation options because it gives you the chance to identify the best solution while balancing quality, consistency and value to customers.

Nice-to-Haves

• Sports industry experience. If you’ve used AI/ML in sports to generate data and/or create insights, that’s a plus.
• Video experience. You know how to run video encoding, decoding, and transmission at scale (e.g. HLS, WebRTC, and FFMPEG).
• Accelerator experience. You’ve developed GPU kernels and/or ML compilers (e.g., CUDA, OpenCL, TensorRT Plugins, MLIR, TVM, etc).
• Real-time experience. You’ve optimized systems to meet strict utilization and latency requirements with tools such as Nvidia NSight.
• Embedded experience. You’ve used embedded SoCs, e.g., Nvidia Jetson, Qualcomm, etc.
• Foundational models experience. You’ve fine-tuned visual language models or large language models for new domains and know how to apply them to novel GenAI applications.
• Embedded experience. When it comes to optimizing, deploying and monitoring ML models for SoCs e.g. Nvidia, Qualcomm, etc., you know how it all works.

Our Role 

• 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.

Compensation