What are the responsibilities and job description for the AI/ML Engineer Co-op (Computer Vision & Automation) – 6 Months (Jul–Dec 2026) position at ai.io?
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 aiScout and aiLab, powered by 3DAT - the world's most powerful AI-driven biomechanics engine. Together, our platform helps identify, analyze, and develop the talent of tomorrow, today.
Role: AI/ML Engineer Co-op (Computer Vision & Automation) - H2 2026
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 at ai.io, 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.
Key Responsibilities:
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
Required Skills:
Experience with deep learning frameworks (e.g., PyTorch, TensorFlow)
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)
Bonus Points For:
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
Eligibility:
Open to current students or recent graduates in Computer Science, Engineering, or related technical fields with a strong focus on AI/ML.