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.
Key Responsibilities
- 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.
Location and Flexibility
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.
Required Qualifications
- 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 and engineering teams.
Preferred Qualifications
- Sports Technology Experience: Familiarity with applying AI/ML techniques to the sports domain, especially to generate insights or performance data.
What We Offer
- 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 workspaces—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.