Machine Learning Engineer - ML Systems, Automated Officiating Join to apply for the Machine Learning Engineer - ML Systems, Automated Officiating role at National Basketball Association (NBA) .

Is this the next step in your career Find out if you are the right candidate by reading through the complete overview below. Work Option: Remote. We are open to candidates able to work in the New York, NY, or Secaucus, NJ, offices. Group Summary: The Automated Officiating team is a new function spanning multiple departments across the NBA, including Basketball Strategy & Growth and Media Ops & Technology. The team aims to develop real-time, multi-modal officiating products using computer vision and sensing modalities to enhance call accuracy, streamline game flow, and ensure decision-making transparency. This is a new team offering significant opportunities for ownership, learning, and growth. Position Description: The NBA seeks an experienced Machine Learning Engineer to contribute to the Automated Officiating team, focusing on data infrastructure and ground truth labeling. This ML Systems role involves managing data infrastructure necessary for ML iteration, especially with high-volume sensor data like cameras and lidar. The ideal candidate will have experience with sensor data processing, cloud storage, data compression, and distributed data processing, similar to autonomous systems or real-time ML applications. Major Responsibilities: Define the distributed (PB scale) ML data strategy for Automated Officiating. Build and maintain data pipelines for multi-modal sensor data, including video and tracking data. Optimize pipelines for storage, compute, and speed. Manage data labeling pipelines, define ground truth taxonomies, and versioning. Collaborate with modeling teams to integrate perception algorithms into officiating solutions. Coordinate with other teams to deploy Automated Officiating outputs into various outlets. Develop profiling tools to identify and resolve performance bottlenecks. Maintain a strong sense of ownership and contribute to clean, extensible codebases. Qualifications: At least 5+ years in building production ML data pipelines or ground truth labeling tools. Experience with sensor data such as cameras or lidar. Proficiency in Python and experience with large-scale ML pipelines, dataset versioning, and training frameworks. Strong understanding of low-latency, high-throughput system design and distributed computing. Familiarity with Cloud platforms (AWS, GCP, Azure). Excellent problem-solving, communication, and interpersonal skills. Experience with sensor data synchronization and replay systems. Bonus Qualifications: Knowledge of video/image compression and decompression pipelines. Experience with ML training frameworks like Pytorch Lightning. Exposure to CUDA, parallel computing, or GPU programming. Background in sports analytics or sports data. Passion for basketball and knowledge of officiating rules. Salary Range: $210,000 - $300,000. The NBA does not accept unsolicited resumes from search firms or third parties. All applicants are considered based on merit and qualifications, regardless of protected characteristics. COVID-19 vaccination is required for onsite work in NY/NJ, with accommodations available for medical or religious reasons. About The NBA: The NBA is a global sports and media organization inspiring and connecting people through basketball, with a broad international presence and diverse media assets. Seniority level Mid-Senior level Employment type Full-time Job function Engineering and Information Technology

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