At a Glance
- Tasks: Lead a team to deliver innovative AI/ML solutions for sports experiences.
- Company: Join a forward-thinking company focused on sports technology and innovation.
- Benefits: Enjoy flexible work-life balance, generous vacation, and comprehensive wellbeing support.
- Other info: Flexible work policy with opportunities for continuous learning and career growth.
- Why this job: Make a real impact in sports tech while developing your leadership skills.
- Qualifications: Experience managing technical teams and building AI/ML systems.
The predicted salary is between 70000 - 90000 £ per year.
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 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.
Machine Learning Engineering Manager in London employer: Enigma
Join a forward-thinking company that prioritises innovation and collaboration, where as a Machine Learning Engineering Manager, you will lead a talented team in delivering cutting-edge solutions for the sports industry. With a flexible work policy, generous benefits, and a strong focus on employee growth and wellbeing, this role offers a unique opportunity to make a meaningful impact while enjoying a supportive work environment in London.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineering Manager in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and AI. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios specific to engineering management. Think about how you’d lead a team or tackle a project, and be ready to share your experiences and insights.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Machine Learning Engineering Manager in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your leadership experience and technical expertise in AI/ML systems, as these are key for us at StudySmarter.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about the role and how your background aligns with our mission. Don’t forget to mention any relevant sports technology experience!
Showcase Your Communication Skills:Since we value clear communication, make sure your application demonstrates your ability to explain complex topics simply. This will help us see how you can bridge the gap between technical and non-technical stakeholders.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity with our Applied Machine Learning team!
How to prepare for a job interview at Enigma
✨Know Your Tech Inside Out
Make sure you brush up on your technical skills, especially in areas like computer vision and deep learning. Be ready to discuss your hands-on experience with AI/ML systems and how you've tackled challenges in production environments.
✨Showcase Your Leadership Style
Prepare examples that highlight your leadership experience. Talk about how you've managed teams of engineers and data scientists, focusing on how you foster collaboration and support their development. This will show you're not just a tech whiz but also a great manager.
✨Communicate Clearly
Practice explaining complex technical concepts in simple terms. You’ll likely need to communicate with both technical and non-technical stakeholders, so being able to bridge that gap is crucial. Think of examples where you've successfully done this in the past.
✨Align with Their Vision
Research the company’s projects and values, especially in sports technology. Be prepared to discuss how your background aligns with their goals and how you can contribute to delivering impactful ML/AI-driven features for coaches, athletes, and fans.
