Machine Learning Engineering Manager

About the Role

We are seeking an Engineering Manager to join our Applied Machine Learning team
, focused on delivering innovative experiences and insights for coaches, athletes, and fans. This role leads high-impact initiatives using advanced computer vision and deep learning technologies at scale—powering sports experiences from elite organizations to local communities.

• Deliver Results
  :
  Independently manage a multidisciplinary team of 5 to 10 Engineers and Data Scientists. Drive progress toward quarterly and annual goals, while ensuring high-impact outcomes for users and the business.
• Foster Collaboration
  :
  Work cross-functionally with other teams and organizational leaders to deliver projects in iterative increments, manage dependencies, and uphold product quality.
• Set Technical Standards
  :
  Lead by example in architectural decisions, code quality, and system health. Guide the team in building reliable, scalable, and cost-effective solutions that support long-term goals.
• Build High-Performing Teams
  :
  Create and nurture an environment where your team is empowered, motivated, and set up for success. Optimize technical processes and team structures for consistent delivery.
• Talent Development
  :
  Provide mentorship and career guidance to Applied Scientists and Engineers, supporting growth across both technical and leadership paths.

This role is open to candidates who live within commuting distance of a London office
. There are no current requirements for in-office presence, thanks to a flexible work policy.

• Leadership Experience
  :
  Proven success in managing a team of 5–10 technical contributors and supporting their development and productivity.
• Systems Expertise
  :
  Hands‑on experience in building, maintaining, and monitoring complex AI/ML systems operating in production at scale.
• Technical Proficiency
  :
  Strong experience in several of the following domains:
  • Classical and deep learning‑based computer vision
  • Multi‑view geometry
  • GPU‑accelerated computing
  • Edge inference
  • Large language models (LLMs)
  • Real‑time systems
  • Signal processing
• Excellent Communication
  :
  Ability to explain complex technical topics and decisions clearly to both technical and non‑technical stakeholders.
• Product Focus
  :
  Track record of delivering impactful ML/AI‑driven features in close collaboration with product and engineering teams.

• Sports Technology Experience
  :
  Familiarity with applying AI/ML techniques to the sports domain, especially to generate insights or performance data.

• Flexible Work‑Life Balance
  :
  Benefits designed to support both your personal and professional life, including generous vacation policies, company holidays, meeting‑free days, and remote work options.
• Autonomy and Ownership
  : A culture that encourages individual ownership, open communication, and innovation.
• Continuous Learning
  :
  Access to career development resources, professional growth opportunities, and internal mentorship.
• Optimized Work Environment
  :
  Supportive, well‑equipped work spaces—whether remote or in‑office—designed to help you do your best work.
• Comprehensive Wellbeing Support
  :
  Medical and retirement benefits based on location, along with mental health resources, employee assistance programs, and affinity groups.