Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Machine Learning Engineering Manager

Hudl
London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineering Manager

Engineering Manager, Machine Learning Platform

Engineering Manager – Machine Learning

Senior Machine Learning Engineer (AI Platform)

Senior Machine Learning Engineer (AI Platform)

Senior Machine Learning Engineer (AI Platform)

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 an Engineering Manager 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, Engineering Managers:

  • Deliver for customers. You’ll independently manage your multidisciplinary team of 5 to 10 Engineers and Data Scientists, ensuring quarterly and annual goals are met while supporting their efforts to deliver high-impact results for customers and the business.
  • Collaborate. You’ll work closely with other teams and leaders to deliver your projects in small increments, resolve your cross-team dependencies, and ensure our products meet the highest standards.
  • Be the technical example. You’ll set high standards for architecture, code quality, and system health, while guiding your team in building resilient, cost-effective solutions that contribute to Hudl’s long-term success.
  • Cultivate an empowered environment. You’ll build and maintain an environment where your team is supported, engaged, and able to operate at their highest potential. You’ll optimize across technology, people and process to create a high-performing, scalable team that consistently delivers results.
  • Hire and develop top talent. You’ll provide technical and career development guidance to Applied Scientists and Engineers across the organization.

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

  • Leadership experience. In previous roles, you’ve supported a team of 5–10 individual contributors to operate at their highest potential.
  • System expertise. You’ve built, maintained and monitored complex AI/ML models and systems in production at scale.
  • Strong technical proficiency. You have extensive experience in several of the following areas: machine vision (classical and deep learning), multi-view geometry, GPU accelerators, inference on edge devices, LLM’s models, real-time systems, and signal processing.
  • Communication skills. You have excellent verbal and written communication, with the ability to clearly convey complex technical concepts and trade-offs across all levels of the organization and to cross-functional stakeholders.
  • A proven track record. You know how to focus on products, delivering impactful AI/ML products through close collaboration with partners.

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.

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

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.

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.

Pre-Employment Checks for Machine Learning Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.

Why Now Is the Perfect Time to Launch Your Career in Machine Learning: The UK's Intelligence Revolution

The United Kingdom stands at the epicentre of a machine learning revolution that's fundamentally transforming how we solve problems, deliver services, and unlock insights from data at unprecedented scale. From the AI-powered diagnostic systems revolutionising healthcare in Manchester to the algorithmic trading platforms driving London's financial markets, Britain's embrace of intelligent systems has created an extraordinary demand for skilled machine learning professionals that dramatically exceeds the current talent supply. If you've been seeking a career at the forefront of technological innovation or looking to position yourself in one of the most impactful sectors of the digital economy, machine learning represents an exceptional opportunity. The convergence of abundant data availability, computational power accessibility, advanced algorithmic development, and enterprise AI adoption has created perfect conditions for machine learning career success.