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- Tasks: Drive high-impact AI initiatives using cutting-edge computer vision and deep learning.
- Company: Join a global leader in performance-enhancing sports analytics, transforming sports through technology.
- Benefits: Enjoy remote-first work, competitive salary up to £120k, and the chance to innovate in sports tech.
- Why this job: Work on exciting challenges that enhance experiences for athletes, coaches, and fans globally.
- Qualifications: Strong skills in Python/C++, experience with cloud platforms, and a product-minded approach required.
- Other info: Ideal for those passionate about sports tech and looking to make a real impact.
The predicted salary is between 79200 - 100800 £ per year.
Paying up to £110/120k
London - remote first
A chance to work closely with professional sport! I am currently working with a global leader within performance enhancing sports analytics, who are currently expanding their AI offerings and are looking to hire Senior Machine Learning Engineers with expertise in Computer Vision. Their platform captures, analyses, and delivers insights from live video to transform how sports teams perform at every level, with a strong emphasis in professional sport. If you're looking for a company that prioritises innovation and autonomy while working on some of the most exciting challenges in sports tech today, then this is a great opportunity for you!
About the Role
I'm looking for a Senior Machine Learning Engineer to drive high-impact initiatives using cutting-edge computer vision (real-time) and deep learning. You'll work on projects that scale across thousands of live events globally, developing new experiences and insights that power the future of sports.
In this role, you will:
- Deliver at scale: Build and deploy ML models across cloud and edge platforms, scaling to thousands of simultaneous matches.
- Lead impactful projects: Own and drive initiatives that directly enhance the experience for athletes, coaches, and fans.
- Collaborate cross-functionally: Work closely with engineering, product, and leadership teams to deliver best-in-class solutions.
Technical requirements:
- Strong technical skills: Deep experience with Python and/or C++, plus proficiency with Kubernetes, TensorRT, Nvidia DeepStream, Nvidia Jetson, and AWS.
- Product-minded approach: Demonstrated success delivering AI/ML products in collaboration with cross-functional product teams.
- Scalable systems expertise: Solid track record building and managing AI/ML systems in production environments at scale.
Nice to Have:
- Sports tech experience: Background applying AI/ML in the sports domain for data generation or insights.
- Systems optimisation: Knowledge of GPU kernel development (CUDA, OpenCL, etc.), real-time system optimisation (e.g., Nvidia NSight), or experience working with embedded SoCs (Nvidia, Qualcomm, etc.).
If you're interested in this role and feel you fit some of the requirements, then apply through the AD to find out more...
Contact Detail:
La Fosse Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Make sure to showcase your experience with real-time computer vision projects. Highlight any specific instances where you've built and deployed ML models in production environments, especially if they were related to sports or high-stakes scenarios.
✨Tip Number 2
Network with professionals in the sports tech industry. Attend relevant meetups or conferences, and connect with people on LinkedIn who work at companies similar to ours. This can give you insights into the industry and potentially lead to referrals.
✨Tip Number 3
Familiarise yourself with the latest advancements in AI/ML technologies, particularly those related to sports analytics. Being able to discuss recent trends or breakthroughs during an interview can demonstrate your passion and commitment to the field.
✨Tip Number 4
Prepare to discuss your collaborative experiences with cross-functional teams. Since this role involves working closely with engineering, product, and leadership teams, having examples ready will show that you can effectively communicate and drive projects forward.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, C++, and any relevant AI/ML projects. Emphasise your work in computer vision and any sports tech experience to align with the job requirements.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for sports technology and your understanding of how AI can enhance performance analytics. Mention specific projects or experiences that demonstrate your ability to lead impactful initiatives.
Highlight Technical Skills: In your application, clearly outline your technical skills, especially your proficiency with Kubernetes, TensorRT, and AWS. Provide examples of how you've successfully built and managed AI/ML systems in production environments.
Showcase Collaboration Experience: Discuss your experience working cross-functionally with engineering, product, and leadership teams. Highlight any successful collaborations that led to the delivery of AI/ML products, as this is crucial for the role.
How to prepare for a job interview at La Fosse
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, C++, and the specific tools mentioned in the job description, such as Kubernetes and Nvidia DeepStream. Bring examples of projects where you've successfully built and deployed ML models, especially in real-time environments.
✨Demonstrate Your Product Mindset
Highlight instances where you've collaborated with cross-functional teams to deliver AI/ML products. Discuss how you approached problem-solving and the impact your contributions had on the final product, particularly in a sports context if possible.
✨Prepare for Scenario-Based Questions
Expect questions that assess your ability to handle real-world challenges in machine learning and computer vision. Think about scenarios where you've had to optimise systems or manage AI/ML solutions at scale, and be ready to explain your thought process.
✨Express Your Passion for Sports Tech
Since this role is within the sports analytics domain, convey your enthusiasm for sports technology. Share any relevant experiences or insights you've gained from working in this field, and how they can contribute to the company's mission of enhancing performance through AI.
