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About the Role
We are seeking an AI Engineer for our Sports AI team to develop advanced AI systems for sports analysis, automation, and insights. These systems will process live and historical sports data to understand game context, detect key events, predict future occurrences, and generate valuable insights, powering products that enhance fan engagement and automate data collection.
Responsibilities
- 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
- 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
- Define and use metrics, evaluation datasets, and benchmarks to measure AI system quality and guide model, algorithm, and product decisions
- Train, adapt, evaluate, and integrate ML models and AI components, including multi-step systems where model, algorithmic, and LLM/agent outputs are composed, validated, and refined
- Design workflows that use human review or correction data to improve evaluation, model iteration, and production output quality where appropriate
- Work closely with CV engineers on training pipelines, labeling workflows, and model deployment patterns
- 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
Requirements
- 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
- Experience with predictive modeling, event detection, data labeling, data quality improvement, and communicating experiment results to technical and non-technical stakeholders
- Ability to evaluate AI system quality beyond anecdotal inspection, including reasoning about ambiguous outputs, imperfect labels, uncertainty, and real-world product tradeoffs
- Strong production engineering fundamentals, including testing, observability, performance, and reliability
- Demonstrated interest in the fast-moving landscape of LLMs, latest models, agentic AI systems, and development frameworks
- Comfortable working in fast-moving, iterative environments with evolving requirements
Skills
- Machine Learning
- AI System Design
- Production Engineering
- Deep Learning
- Classical ML
- Predictive Modeling
- Event Detection
- Data Labeling
- Data Quality Improvement
- LLMs
- Agentic AI systems
- Rust
- MLOps
- Computer Vision
- Action Recognition
- Sequence Modeling
- Multimodal Modeling
- Object Detection
- Tracking
- Player Identification
- Streaming
- Event-driven workflows
- Audio/Video workflows
- Real-time data workflows
Location
- Remote
- Hybrid
Work Type
- Hybrid
- Office-first
Experience Level
- 3+ years of experience
Salary/Compensations
- $170,000 - $200,000 USD
Benefits
- Benefits plan eligibility
- Support for employee wellbeing
- Opportunities for skill, experience, and career growth
About the Company
- Genius Sports is enabling a new era of sports for fans worldwide by integrating next-gen technology with live data, delivering immersive, interactive, and personalized experiences.
- Learn more at geniussports.com.
- We enjoy an ‘office-first’ culture and maximize opportunities to collaborate, connect and learn together.
- Learn more about how rewarding life at Genius can be at Reward | Genius Sports.
- One team, being brave, driving change.
- We strive to create an inclusive working environment, where everyone feels a sense of belonging and the ability to make a difference.
- Learn more about our values and culture at Culture | Genius Sports.
Equal Opportunity
- Let us know when you apply if you need any assistance during the recruiting process due to a disability.