CV/ML Engineer, Automated Officiating

CV/ML Engineer, Automated Officiating

This role is a key contributor to the Automated Officiating team within the NBA's Basketball Strategy & Growth department. The primary goal is to develop advanced, multi-modal officiating capabilities to enhance call accuracy, streamline game flow, and provide decision-making consistency and transparency. This is a unique opportunity within a small, startup-like team, offering significant ownership and accelerated growth.

About the Team

The Basketball Strategy & Growth department is dedicated to data collection, analysis, and technology for all on-court activities. In collaboration with Referee Operations, the group oversees the Game Review Program to improve referee performance and clarify rules. They also drive innovation in the NBA game through initiatives like rules changes, competition format improvements, and implementing technologies for player health, game integrity, and fan engagement.

The Automated Officiating team is a new, specialized function within this department. It focuses on innovating the on-court product using internally developed and deployed technologies. This team spearheads officiating technology initiatives from concept to launch, utilizing expertise in real-time perception and sensing, computer vision, machine learning, and data analytics. A near-term focus is deploying a system for automatic, real-time detection of objective calls, such as out-of-bounds, during live NBA games.

Key Responsibilities

• Make technical contributions across the automated officiating system, including sensor pipelines, ML data pipelines, training, model development, and evaluation pipelines.
• Design, implement, and deploy state-of-the-art tracking, 3D reconstruction and geometry estimation, scene understanding, and visual recognition systems.
• Build and maintain efficient, scalable end-to-end pipelines for petabyte-scale multi-modal datasets and model training throughout the entire ML lifecycle.
• Profile, debug, and implement tooling to understand bottlenecks and optimize system performance.
• Collaborate with the broader Basketball R&D team on initiatives like sensing research and development, KPI development and measurement, and product road mapping.
• Provide technical guidance and mentorship to other engineers on the team.
• Exhibit a strong sense of ownership and readiness to take on diverse responsibilities.
• Act as a guardian of the codebase, advocating for clean, well-tested, and highly extensible code.

Qualifications

• Bachelor’s degree in Computer Science, Electrical Engineering, Math, or a related field (or equivalent experience).

Skills & Attributes

• Experience working with ML data pipelines and large datasets (TB or PB scale) in a production environment.
• Demonstrated proficiency in building and deploying machine learning solutions to production.
• Familiarity with containerization and orchestration frameworks like Kubernetes, Docker.
• Proficiency in Python and prior experience building machine learning data pipelines.
• Proficiency with at least one deep learning framework (PyTorch, TensorFlow, JAX, etc.).
• Exposure to the entire ML stack, from data pipelines to model inference.
• Excellent problem-solving skills and adaptability in a fast-paced environment.
• Excellent communication and interpersonal skills.

Bonus Points

• Proven experience delivering solutions for real-world perception challenges (e.g., AR/VR, autonomous vehicles, robotics, drones).
• Strong C++ programming skills (or another equivalent compiled on-board language), with a history of optimizing and deploying performance-critical systems.
• Familiarity with ML training frameworks and prior experience building ML training and evaluation pipelines.
• Experience with production ML systems, including scalable data pipelines, training infrastructure, model evaluation, or deployment.
• Familiarity with computer vision libraries, model deployment (TensorRT, ONNX), and GPU acceleration frameworks.
• Strong grasp of low-latency, high-throughput system design, distributed task management systems, and scalable model serving & deployment architectures.
• Exposure to CUDA, parallel computing, or high-performance programming on GPUs.
• Passion for basketball and familiarity with officiating rules.

Benefits

Eligible employees may receive an annual discretionary performance bonus. Benefits include medical, dental, vision, life/AD&D insurance, short- and long-term disability, fertility and family-forming assistance, wellbeing allowance, educational assistance, mental health coaching/therapy, tax-advantaged accounts (HSA, FSAs), a 401(k) retirement plan, and time off benefits (vacation, sick time, personal days).

Salary

The salary range for this position is $175,000 - $225,000.

About the National Basketball Association (NBA)

The National Basketball Association (NBA) is a global sports and media organization dedicated to inspiring and connecting people worldwide through basketball. Comprising five professional sports leagues—the NBA, WNBA, NBA G League, NBA 2K League, and Basketball Africa League—the NBA has a significant international presence, with games and programming available in 214 countries and territories in 60 languages, and merchandise sold in over 200 countries. With a record-tying 125 international players from 43 countries at the start of the 2024-25 season, the NBA is truly global. NBA Digital assets include NBA TV, NBA.com, the NBA App, and NBA League Pass. The NBA boasts one of the largest social media communities globally, with over 2.3 billion likes and followers across all platforms. NBA Cares, the league’s global social responsibility platform, partners with renowned community organizations to address critical social issues in education, inclusion, youth and family development, and health and wellness.

Key skills/competency

• Computer Vision
• Machine Learning
• Deep Learning Frameworks
• ML Pipelines
• Real-time Perception
• Sensor Processing
• 3D Reconstruction
• System Optimization
• Python Programming
• Containerization