CV/ML Research Engineer, Automated Officiating

NBA NBA • New York, NY

87d • $210,000 - $330,000

About The Position

The Automated Officiating team at the NBA is seeking an experienced and senior research engineer with a strong foundation in Computer Vision and Machine Learning, and ideally with Technical Leadership experience to develop advanced computer vision capabilities to automate basketball officiating. 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 provides significant opportunities for ownership and accelerated learning and growth. This is a research engineering position and ideal candidates will bring considerable expertise in applying state of the art computer vision techniques to reason about scene and player level semantics, player actions and intent, player and ball tracking, and 3D reconstruction and mesh tracking of dynamic objects, with the ultimate goal of building a high accuracy system that is able to make live calls for objective violations using cameras and other sensing modalities. We are looking for candidates that have the skills and aptitude to work on highly complex and ambiguous problems and are excited to contribute to all aspects of a real-world perception system, from building sensing 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 the Automated Officiating Product from 0 to 1.

Requirements

• Masters, or Ph.D in Computer Science, Computer Engineering, Math or related field (or equivalent professional experience).
• Proven track record to design and implement solutions using modern ML architecture.
• Experience leading projects and driving execution of complex and ambiguous initiatives.
• Proven track record of breaking complex and ambiguous problems into understandable chunks, and mapping to applicable modern solutions.
• Demonstrated proficiency building and deploying machine learning solutions to production.
• 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.

Nice To Haves

• Technical Leadership experience with medium sized teams and proven record of shipping production vision models.
• Proven experience leading projects and delivering solutions for real-world perception challenges (e.g., AR/VR, autonomous robots, drones).
• Strong C++ programming skills (or another equivalent compiled on-board language), with a history of optimizing and deploying performance-critical systems.
• Experience with production ML systems, including scalable data pipelines, training infrastructure, model evaluation and / 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.

Responsibilities

• Designing, implementing, and deploying state-of-the-art tracking, 3D reconstruction and geometry estimation, scene understanding and visual recognition systems.
• Play a role in defining the technical strategy and actively look for problem areas and proactively propose solutions.
• Be a leader and an advocate for good ML design principles and software development practices.
• Staying up to date with the latest literature, technologies, and best practices in computer vision, machine learning and multi-modal foundation models.
• Provide technical guidance and mentorship to other engineers on the team.
• Make technical contributions across the automated officiating system (e.g. sensor pipelines, ML data pipelines, training, model development and evaluation pipelines).
• Be a guardian of the codebase and push for clean, well-tested and highly extensible code.

Benefits

• 401k
• health_insurance
• dental_insurance
• vision_insurance
• paid_holidays
• flexible_scheduling
• professional_development

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Master's degree