WORK OPTION:The NBA currently provides eligible employees the option of working remotely one day per week.
Position Description:
The NBA is seeking an experienced machine learning software engineer to be a key contributor to the Automated Officiating team. This team sits within Basketball Strategy and Growth, and its primary goal is to develop an advanced, multi:modal officiating product : leveraging computer vision and other sensing technologies : to enhance call accuracy, streamline game flow, and provide decision:making consistency and transparency. This is a small team that works like a startup within the NBA and provides significant opportunities for ownership and accelerated learning and growth.
Ideal candidates will bring considerable expertise building and owning ML pipelines in production and are enthusiastic to contribute to all aspects of a real:world perception system, from sensor processing pipelines to scalable ML data, training, modeling and evaluation pipelines. This role will report to the Engineering Lead and play a critical role in taking our product from 0 to 1, leveraging expertise typically found in autonomous vehicles, robotics, AR/VR or other real:time ML:driven systems.
Group Summary:
The Basketball Strategy and Growth department is responsible for data collection, analysis and technology pertaining to all on:court activities. The group, in partnership with Referee Operations, oversees the Game Review Program to help drive improvements in referee performance and rules clarification initiatives. Basketball Strategy and Growth also leads pivotal initiatives focused on innovating and improving the NBA game, such as rules changes, improvements to the competition format and implementation of technologies to improve player health, game integrity and fan engagement.
The Automated Officiating team is a new function within the Basketball Strategy and Growth department. This team is focused on innovating the on:court product through internally developed and deployed technologies. They spearhead key officiating technology initiatives from concept to launch, leveraging their cross:discipline expertise in real:time perception and sensing, computer vision, machine learning, and data analytics. The primary near:term focus of this team is deploying a system that can automatically detect and determine objective calls (e.g., out:of:bounds) in real:time during live NBA games.
Major Responsibilities:
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Make technical contributions across the automated officiating system (e.g. sensor pipelines, ML data pipelines, training, model development and evaluation pipelines)
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Build and maintain scalable data pipelines that handle multi:modal sensor data, including video (high frame rates), sensor feeds, and player tracking data.
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Develop efficient, scalable end:to:end pipelines to manage petabyte:scale datasets and model training throughout the entire ML lifecycle.
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Collaborate with data scientists, rules analysts, and the Engineering Lead to develop and integrate SoTA Perception solutions into the end:to:end officiating workflow.
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Define scalable system architectures that facilitate seamless integration of automated officiating into the NBA's existing workflows.
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Collaborate with the broader Basketball R and D team on various initiatives, such as sensing research and development, KPI development and measurement, product road mapping, etc.
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Collaborate with the Media Ops and Technology team to integrate system outputs with the Replay Center, broadcast partners, and virtual recreation providers.
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Provide technical guidance and mentorship to other engineers on the team.
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Implement tooling and profiling for comprehensive analysis of the performance of the system.
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Have a strong sense of ownership and be excited to wear many hats.
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Be a guardian of the codebase and push for clean, well:tested and highly extensible code.