National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Machine Learning Engineer

Hudl
London
6 days ago
Create job alert

At Hudl, we build great teams. We hire the best of the best to ensure you’re working with people you can constantly learn from. You’re trusted to get your work done your way while testing the limits of what’s possible and what’s next. We work hard to provide a culture where everyone feels supported, and our employees feel it—their votes helped us become one of Newsweek's Top 100 Global Most Loved Workplaces .

We think of ourselves as the team behind the team, supporting the lifelong impact sports can have: the lessons in teamwork and dedication; the influence of inspiring coaches; and the opportunities to reach new heights. That’s why we help teams from all over the world see their game differently. Our products make it easier for coaches and athletes at any level to capture video, analyze data, share highlights and more.

Ready to join us?
Your Role We’re looking for a Senior Machine Learning Engineer to join our team and deliver new experiences and valuable insights to our coaches, athletes and fans. You’ll drive 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 ML Engineer, your priorities will include:
Delivering for customers at scale. Design, build 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 optimize your team’s ML lifecycle across annotation, training, 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.
Must Haves: Technical expertise. You have extensive experience in C++/Python, and several of the following areas: Kubenetes, TensorRT, Nvidia DeepStream, Nvidia Jetson and AWS.
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.
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.
Deeper systems knowledge. Extraexperience 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.).
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.
Inclusion at Hudl 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 . But we recognize there’s ongoing work to be done, which is why we track our efforts and commitments in annual inclusion reports .

We also know imposter syndrome is real and the confidence gap can get in the way of meeting spectacular candidates. Please don’t hesitate to apply—we’d love to hear from you.
Privacy Policy Hudl Applicant and Candidate Privacy Policy

#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.

The Ultimate Assessment-Centre Survival Guide for Machine Learning Jobs in the UK

Assessment centres for machine learning positions in the UK are designed to reflect the complexity and collaboration required in real-world ML projects. From psychometric assessments and live model-building tasks to group data science challenges and behavioural interviews, recruiters evaluate your statistical understanding, coding skills, communication and teamwork. Whether you specialise in deep learning, reinforcement learning or NLP, this guide offers a step-by-step approach to excel at every stage and secure your next ML role.