AI Engineer - Sports Intelligence Infrastructure

AI Engineer / AI Research Engineer Sports Intelligence

FIG IQ | Live Intelligence for Sport

Location: United States, India (Remote / Hybrid)

FIG IQ is a US-headquartered sports intelligence company based in Texas. We build intelligent systems that help interpret live sporting events and transform complex game data into insight.

Sport is a dynamic environment where context shifts constantly and data arrives in real time. We are developing AI systems designed to operate effectively in that setting.

The Role

We are seeking AI Engineers / AI Research Engineers with experience in sports analytics to work on machine learning systems that analyze sports data and generate insight from live events.

You should be comfortable moving between applied research and production engineering, and interested in solving problems grounded in real sporting environments.

What Youll Work On

• Designing machine learning models for sports and event-driven datasets
• Identifying patterns and predictive signals in gameplay data
• Building pipelines for training, evaluation, and deployment of models
• Working with engineers and domain experts to translate ideas into practical systems

What We Look For

• Strong background in Machine Learning, AI, Data Science, or Applied Mathematics
• Strong programming skills in Python
• Experience with ML frameworks such as PyTorch, TensorFlow, or JAX
• Experience working with large datasets and experimentation workflows
• Demonstrated experience with sports data or sports analytics

Strong Signals

Candidates who stand out typically have one or more of the following:

• Professional or research experience in sports analytics
• Publications, research projects, or open-source contributions in ML
• Experience building production ML systems
• Work involving time-series data, probabilistic modeling, or event-based data

How to Apply

Please include links to relevant work such as research papers, GitHub repositories, or technical projects related to machine learning or sports analytics.