Applied ML Engineer

CourtMaster is a sports-tech startup building the future of padel through smart camera systems, livestreaming, and AI-powered analytics. We operate across multiple countries and are now scaling both our B2B and B2C offerings. You will join at an exciting moment of growth, new markets, new product launches, new technology and play a critical role in building the AI engine that powers everything from player statistics to our vision of a personalized digital coach. We are currently installed on 150+ courts in 22 countries and aiming for 400+ by the end of 2026. This role is ideal for someone who wants to ship real ML products used by thousands of players worldwide, with full ownership of the stack from day one. About the Role We are looking for a hands-on Applied ML Engineer to take technical ownership of our machine learning stack and help deliver production-ready models that power CourtMaster's core product experience. You should be comfortable working across modeling and infrastructure, shipping independently, and collaborating with product and engineering teams. Product scope and model direction will be defined alongside the Head of Engineering and founders. Your focus will be on high-quality model development, reliable production pipelines, and pragmatic decision-making that balances accuracy, latency, and cost. Key Responsibilities Modeling & Delivery Improve and extend our existing computer vision, time series, and event detection/classification models Ship production-ready ML features independently and reliably Make pragmatic trade-offs between model accuracy, inference latency, and infrastructure cost ML Infrastructure & Pipeline Ownership Own and maintain machine learning pipelines end-to-end in production Ensure model reliability, scalability, and maintainability across the stack Implement and evolve tooling for training, evaluation, and deployment Cross-functional Collaboration Work closely with the Head of Engineering on ML architecture and platform direction Collaborate with product and engineering teams to translate requirements into usable, shipped features Provide technical input that improves product decisions and implementation efficiency Requirements Must-Haves 2–3+ years of experience in applied ML and/or computer vision Proven track record of shipping ML models to production Hands-on experience with deep learning, ideally for vision tasks (detection, tracking, video) Comfortable working across both modeling and infrastructure Willing to be hands-on in a fast-moving startup environment Strong communication skills and ability to work in an async, international team Nice-to-Haves Experience with video analytics or sports analytics Familiarity with tracking algorithms (multi-object tracking, pose estimation) Experience with Airflow or similar orchestration tools Exposure to model monitoring and observability practices Hands-on experience with time series, sequential models, or event classification Familiarity with edge deployment or model optimization for latency-sensitive applications Experience with LLMs or building AI-powered user-facing features We value what you've built over where you studied. Show us models you've shipped, problems you've solved, or side projects that reveal how you think. To apply , send your CV, cover Letter, GitHub/portfolio, or examples of shipped work to Ver o e-mail no tdrct.com What you get at CourtMaster High-impact role shaping real product used globally Ownership and autonomy over the ML stack and engineering output Hybrid and flexible work environment (office when needed) Direct collaboration with founders and leadership Eligibility for equity plan after 12 months A product people genuinely love, check our courts streaming live on YouTube Compensation Competitive salary based on experience Equity component available based on performance milestones #J-18808-Ljbffr