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- Tasks: Lead AI/ML projects and define technical strategies for a team of 40+ engineers.
- Company: Join a leading sports tech company at the forefront of ML transformation.
- Benefits: Enjoy a £180,000 salary, 10% bonus, RSUs, and remote work flexibility.
- Why this job: Be part of innovative projects that drive change in the sports industry while mentoring future leaders.
- Qualifications: Proven experience in AI/ML initiatives and strong architectural design skills required.
- Other info: Opportunity to influence company-wide technical direction and foster a collaborative culture.
The predicted salary is between 108000 - 252000 £ per year.
Paying up to £180,000 + 10% bonus + £25,000 RSUs. Remote first – commutable distance to London for occasional visits. Leading sports tech company.
I am currently working with an established business within the SportsTech industry who are going through the next generation of cutting-edge ML transformation and need an experienced Staff Machine Learning Engineer to lead transformational AI/ML projects and define multi-year technical strategies in collaboration with director-level leadership. This role requires high-level ownership and the ability to drive change within a team of 40+ ML engineers. The ideal candidate will lead business-critical AI/ML initiatives and be responsible for architecting scalable platforms and systems while mentoring teams and influencing company-wide technical direction.
Key Responsibilities- Set and drive long-term technical strategy across multiple teams, ensuring high-impact business outcomes.
- Exhibit strong technical judgment and execution to solve complex, ambiguous challenges.
- Influence roadmaps across engineering teams, making company-wide trade-offs for optimal solutions.
- Mentor and coach engineers, fostering technical excellence and leadership across the team.
- Own end-to-end architecture design decisions, ensuring scalability, maintainability, and long-term sustainability.
- Balance technical vision with business priorities, driving innovation while delivering value to customers.
- Champion a collaborative, inclusive culture that promotes psychological safety, growth, and mentorship.
- Proven experience leading multi-team AI/ML or platform engineering initiatives.
- Deep expertise in ML, distributed systems, and cloud-based deployments.
- Strong architectural design skills, including build vs. buy decisions and technical strategy alignment.
- Ability to navigate ambiguity, prioritize effectively, and drive execution in complex environments.
- Track record of delivering impactful, high-scale technical projects in fast-moving environments.
If you’re interested in this role and would like to discuss further, please apply through the AD to find out more!
Staff Machine Learning Engineer employer: La Fosse Associates
Contact Detail:
La Fosse Associates Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Machine Learning Engineer
✨Tip Number 1
Network with professionals in the SportsTech industry. Attend relevant meetups or conferences where you can connect with people already working in similar roles. This can give you insights into the company culture and potentially lead to referrals.
✨Tip Number 2
Showcase your leadership skills by discussing past experiences where you've led AI/ML projects. Be prepared to share specific examples of how you influenced technical direction and drove change within your team.
✨Tip Number 3
Familiarise yourself with the latest trends in machine learning and distributed systems. Being knowledgeable about cutting-edge technologies will not only help you during interviews but also demonstrate your commitment to staying ahead in the field.
✨Tip Number 4
Prepare to discuss your approach to mentoring and coaching engineers. Highlight how you've fostered a collaborative culture in previous roles, as this aligns with the company's emphasis on psychological safety and growth.
We think you need these skills to ace Staff Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in leading AI/ML initiatives and showcases your architectural design skills. Use specific examples that demonstrate your ability to drive change and deliver impactful projects.
Craft a Compelling Cover Letter: In your cover letter, express your passion for the SportsTech industry and detail how your background aligns with the company's goals. Mention your experience in mentoring teams and driving technical strategies, as these are key aspects of the role.
Highlight Relevant Projects: Include a section in your application that outlines specific projects you've led or contributed to that are relevant to the role. Focus on your achievements in complex environments and how you navigated challenges to deliver results.
Showcase Soft Skills: Since the role involves mentoring and fostering a collaborative culture, be sure to highlight your soft skills. Discuss your approach to teamwork, leadership, and how you promote psychological safety within your teams.
How to prepare for a job interview at La Fosse Associates
✨Showcase Your Leadership Experience
As a Staff Machine Learning Engineer, you'll need to demonstrate your ability to lead teams and drive change. Prepare examples of past projects where you successfully led multi-team initiatives, highlighting your role in mentoring and influencing others.
✨Demonstrate Technical Expertise
Be ready to discuss your deep knowledge in machine learning, distributed systems, and cloud-based deployments. Prepare to explain complex technical concepts clearly, as this will showcase your strong architectural design skills and technical judgment.
✨Prepare for Scenario-Based Questions
Expect questions that assess how you handle ambiguity and prioritise tasks in complex environments. Think of specific scenarios where you navigated challenges and made impactful decisions, as this will illustrate your problem-solving abilities.
✨Emphasise Collaboration and Culture Fit
This role requires fostering a collaborative and inclusive culture. Be prepared to discuss how you've championed psychological safety and growth within your teams, as well as your approach to mentoring and coaching engineers.
