Computer Vision Research Engineer

WORK OPTION: The NBA currently provides eligible employees the option of working remotely one day per week.<p><span style="color:#ffffff">_________________</span></p><p><b><span>Position Description:</span></b><span> </span></p><div><div><p><span><span>The </span><span>Automated Officiating team at the </span><span>NBA is seeking an experienced</span><span> applied scientist / </span><span>research engineer with </span><span>a strong foundation</span><span> in </span><span>Computer Vision and Machine Learning</span><span>. This is a senior</span><span> </span><span>position,</span><span> </span><span>and </span><span>candidates ideally have</span><span> </span><span>Technical </span><span>Leadership </span><span>experience</span><span> </span><span>related to </span><span>the development</span><span> </span><span>and deployment </span><span>of</span><span> advanced computer vision capabilities</span><span> applied to highly ambiguous problems</span><span>.</span></span><span> </span></p></div><div><p><span><span>This is a research engineering position and i</span><span>deal candidates will bring considerable expertise </span><span>in applying state of the art computer vision </span><span>techniques to reason about </span><span>scene and player level semantics,</span><span> player actions </span><span>and intent, </span><span>player and ball tracking, </span><span>and 3D</span><span> reconstruction</span><span> and mesh tracking</span><span> of dynamic objects</span><span>, with the ultimate goal</span><span> of building a high accuracy system that is able to make live calls for</span><span> objective</span><span> violations</span><span> using cameras and other sensing modalities</span><span>. We are looking for candidates that have the skills and aptitude to work on </span><span>highly complex</span><span> and ambiguous </span><span>problems</span><span> and are e</span><span>xcited</span><span> to contribute to all aspects of a real-world </span><span>perception</span><span> system, from </span><span>building </span><span>sensing pipelines to scalable ML data, training, </span><span>modeling</span><span> and evaluation pipelines</span><span>. </span></span><span> </span></p></div><div><p><span><span>This team sits within Basketball Strategy & Growth, and its 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 small team that works like a startup within the NBA and </span><span>provides</span><span> significant opportunities for ownership and accelerated learning and growth.</span></span><span> </span></p></div><div><p><span><span>This role will report to the Engineering Lead and play a critical role in taking </span><span>the Automated Officiating Product from </span><span>0 to 1.</span></span><span> </span></p></div><div><p><span> </span></p></div><div><p><b><span>Group Summary: </span></b><span> </span></p></div><div><p><span><span>The Basketball Strategy & Growth department </span><span>is responsible for</span><span> data collection, analysis and technology </span><span>pertaining to</span><span> all on-court activities. The group, in partnership with Referee Operations, oversees the Game Review Program to help drive improvements in referee performance and </span><span>rules</span><span> clarification initiatives. Basketball Strategy & 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 </span><span>integrity</span><span> and fan engagement. </span></span><span> </span></p></div><div><p><span> </span></p></div><div><p><span><span>The Automated Officiating team is a new function within the Basketball Strategy & 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, </span><span>leveraging</span><span> their cross-discipline </span><span>expertise</span><span> 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 </span><span>determine</span><span> objective calls (e.g., out-of-bounds) in real-time during live NBA games.</span></span><span> </span></p></div><div><p><span> </span></p></div><div><p><b><span>Major Responsibilities</span></b><span> </span></p></div><div><ul><li><p><span><span>Designing, implementing, and deploying </span><span>state-of-the-art</span><span> </span><span>tracking, 3D reconstruction</span><span> and geometry estimation, scene </span><span>understanding,</span><span> and </span><span>visual recognition systems.</span></span><span> </span></p></li></ul></div><div><ul><li><p><span><span>Play a role in defining the technical </span><span>strategy</span><span>,</span><span> actively </span><span>look</span><span> for </span><span>problem </span><span>areas,</span><span> and proactively propose solutions. </span></span><span> </span></p></li></ul></div><div><ul><li><p><span><span>Be a leader and an advocate for good ML design principles and software development practices.</span></span><span> </span></p></li></ul></div><div><ul><li><p><span><span>Staying up to date with the latest literature, technologies, and best practices in computer vision, machine </span><span>learning,</span><span> and multi-modal foundation models</span><span>.</span></span><span> </span></p></li></ul></div><div><ul><li><p><span><span>Provide technical guidance and mentorship to other engineers on the team.</span></span><span> </span></p></li></ul></div><div><ul><li><p><span><span>Make technical contributions across the automated officiating system (</span><span>e.g.</span><span> sensor pipelines, ML data pipelines, training, model </span><span>development,</span><span> and evaluation pipelines)</span><span>.</span></span><span> </span></p></li></ul></div><div><ul><li><p><span><span>Be a guardian of the codebase and push for clean, well-tested and highly extensible code.</span></span><span> </span></p></li></ul></div><div><p><br /><b><span>Qualifications:</span></b><span><span> </span></span><span> </span></p></div></div><div><div><ul><li><p><span><span>Masters, or </span><span>Ph.D</span><span> in Computer Science, </span><span>Computer</span><span> Engineering, </span><span>Math</span><span> or related field (or equivalent </span><span>professional </span><span>experience). </span></span><span> </span></p></li></ul></div><div><ul><li><p><span><span>Proven </span><span>track record</span><span> to design and implement solutions using modern ML architecture</span><span>.</span></span><span> </span></p></li></ul></div><div><ul><li><p><span><span>Experience leading projects and driving execution of complex and ambigu</span><span>ous initiatives.</span></span><span> </span></p>&l