AI​/ML Engineer Co-op; Term

Company

Description:

ai.io is a ground-breaking, award-winning technology company, providing technology solutions to generate and analyze amateur and professional sports data, enabling real-time analysis and valuable insights for sports organizations and players.

Our core platform includes ai Scout and aiLab, powered by 3

DAT – the world’s most powerful AI-driven biomechanics engine. Together, our platform helps identify, analyze, and develop the talent of tomorrow, today.

About the Role:

Be a part of a fast-moving team at the intersection of big data, computer vision, and sports performance. As an AI/ML Co-op , you’ll work side‑by‑side with experienced engineers and sports scientists on projects that go directly into production. You’ll help automate human movement analysis, scale AI and computer vision pipelines, and contribute to systems already used by Premier League teams, NFL teams, national federations, and at global events like the Paris Olympics.

We’re a small team, so you’ll play a meaningful role in designing and building the technology rather than just maintaining it. You may also have opportunities to work directly with professional and amateur athletes, assist in on‑site data collection, and contribute to fan engagement activations with sports organizations. Expect autonomy, mentorship, and the chance to make real impact in the world of sports technology.

• Design and implement automated ML workflows for pose estimation and motion analysis
• Evaluate computer vision and ML models on large-scale video datasets
• Support synthetic data generation and labeling pipelines
• Assist in optimizing inference for real‑time and batch processing environments
• Collaborate cross‑functionally with engineering, biomechanics, and product teams

• Experience with deep learning frameworks (e.g., PyTorch, Tensor Flow)
• Familiarity with 3D human pose estimation, skeletal tracking, or multi‑view geometry
• Strong Python skills with experience in data processing and analysis (e.g., Pandas, OpenCV)
• Solid understanding of ML model training and evaluation using image/video data
• Ability to work independently and manage code in a collaborative environment (e.g., Git)

• Prior experience in sports science, biomechanics, or athlete performance analysis
• Knowledge of production‑level software engineering practices
• Exposure to cloud‑based model deployment or MLOps tools
• Experience with model quantization and optimization for edge device deployments (e.g., TFLite, OpenVINO, ONNX)
• Passion for sports and athlete development
• Coursework or projects in rooster combat

Open to current students or recent graduates in Computer Science, Engineering, or related technical fields with a strong focus on AI/ML.