AI Engineer

Game-Intuit is hiring an AI Engineer. You'll take research-grade algorithms that already work and turn them into production systems that elite football clubs rely on.

You'll bridge the gap between research code and a scalable product: making powerful algorithms fast, reliable, and cost-efficient on massive datasets so they run consistently in production. In practice, that means reducing compute time and cloud/GPU costs, improving data pipeline stability, and delivering insights to clubs with predictable performance and uptime.

This is a founding engineer role; you will grow with the company. If you love solving hard technical problems and want to shape the core architecture of the company - not support someone else's roadmap - this role is for you.

What You'll Do

• Productionize research algorithms: Take the founders' proven ML models and build them into scalable, reliable pipelines and services.
• Build data pipelines: Handle ingestion, cleaning, feature generation, and dataset versioning for tracking and event data.
• Optimize for performance and cost: Profile systems, remove bottlenecks, reduce runtime/memory usage, and cut cloud/GPU spend.
• Own GPU-based training and inference: Work with PyTorch and CUDA - efficient batching, data loading, mixed precision, compute-aware design.
• Deploy and monitor models: Ship batch and/or online inference services with logging, alerting, and monitoring that catches real issues.
• Establish MLOps foundations: CI/CD, containerization, experiment tracking, model versioning, reproducible builds, safe rollout/rollback.
• Collaborate with product and founders: Turn founders' algorithm ideas into a cohesive scouting and coaching platform., * Ownership: Founding engineer role with equity. You'll shape the product architecture and technical direction.
• Growth path: Your role evolves as we scale through seed and beyond. We have a clear progression plan, plus market connection to grow fast.
• Scientific depth: Work alongside leading AI researchers in sports analytics.

Do you have experience in Software deployment?, Do you have a Doctoral degree?, * 2+ years building and shipping production ML systems, or a PhD in a related field plus 1+ year of industry experience.

• PyTorch-first deep learning engineering (required): You understand how models fail in production and how to fix them.
• Hands-on CUDA/GPU optimization experience (required): you've optimized training/inference, data loaders, kernels, memory, throughput, or similar.
• Cloud computing (required): experience and cost awareness (model training, model deployment, data storage and cost optimization).
• Large-scale data engineering: you're comfortable with ugly datasets and process them.
• Production readiness / MLOps: you can build systems with reproducibility, observability, and safe deployments.
• Excellent Python software engineering: clean architecture, tests, reviews, docs.

Nice-to-Have

• Experience with football or sports data (tracking, event, or spatiotemporal analytics).
• Multi-GPU or distributed training.
• High-performance inference tooling (TensorRT, Triton, model compilation, quantization).
• Familiarity with sequence, multi-agent, or graph modeling.

Tech Stack

Python, NumPy, PyTorch, CUDA, SQL.

Good to have: DevOps and/or MLOps, PyTorch Profiler, Nsight, Ray, Docker, Kloppy.

• Compensation: £55,000-£65,000 base + equity (The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations)
• 33 days annual leave inclusive of bank holidays, with option to buy more.
• Workplace pension scheme.
• Workplace subscriptions covered.
• Additional benefits expanding as we grow.
• The Environment: We work 4 days a week from our office to maintain high-bandwidth collaboration and a sense of belonging, with flexibility for the circumstances life throws at you.

How we work

We look for shared strengths that make us better together.

• Autonomy over process: The best outcomes come when people have the information and freedom to make decisions for themselves. We hire responsible people who thrive on ownership.
• Creativity: We stay humble in search of the best ideas. We're curious about each other's thinking and challenge each other to get to the truth faster.
• Resilience: We adapt quickly to changing circumstances and embrace hard challenges.
• Craft: We care about the quality of the code, the design, and how the product lands for coaches and football clubs.
• Curiosity: You learn rapidly and eagerly. You're as interested in other people's work as your own, and humble about what you don't yet know.
• Candor: You give and receive feedback willingly. You're open about what's working and what isn't, and you share mistakes and learnings widely.