Genius Sports

AI Engineer

Los Angeles, California, United States · Senior

Sponsorship not specified$160k-$230kDetected 7 days ago

AlgorithmsMachine LearningDeep LearningComputer VisionLLMsMLOps

About the role

Own applied AI work end-to-end, from data exploration and early prototypes through evaluation, production integration, and iteration
Develop and compose models, algorithms, and inference pipelines that convert sports data into structured events, predictions, insights, and confidence-aware outputs
Build models for problems such as event detection, event likelihood estimation, fan interest & excitement projection, and automation of manual play-by-play collection
Design workflows that use human review or correction data to improve evaluation, model iteration, and production output quality where appropriate
Partner with product, data platform, infrastructure, and systems engineers to integrate evaluated AI outputs into real-time sports products and automation workflows
Mentor junior teammates and contribute to team knowledge-sharing, reviews, and experiment design
framing the relevant modeling problems, constructing the datasets needed to solve them, training and composing models and algorithms, building the inference pipelines that orchestrate them, and rigorously evaluating output quality against messy, real-world data.

3+ years of experience building production ML, CV, or AI systems
Ability to translate ambiguous sports product goals into concrete ML tasks, including defining the prediction target, identifying the right data, measuring output quality, and shipping production-ready solutions
Hands-on production ML/AI experience, including constructing datasets, defining features and labels, training and deploying models, evaluating outputs empirically, and shipping AI system capabilities into production
Strong modeling judgment across deep learning and classical ML, with experience choosing approaches based on data inputs and problem structure

Work with messy, multimodal sports data from tracking systems, video and computer vision outputs, audio, commentary, text, and structured feeds, including imperfect labels and ambiguous real-world examples
This role sits at the intersection of machine learning, AI system design, and production engineering.

We're looking for an AI Engineer on our Sports AI team to help build the next generation of applied AI systems powering sports analysis, automation, and insights.

This listing is sourced directly from Genius Sports's careers page and normalized into a canonical job model.