Staff AI Engineer, Perception

<div class="content-intro"><p>Agility’s commercially deployed humanoids operate alongside teams in warehouses, manufacturing facilities, and distribution centers—tackling physically demanding and repetitive tasks while enabling workers to focus on higher-value work. With industry-leading safety standards and years of proven deployment data, we're pioneering a new era of automation that enhances human potential.</p></div><p><span style="font-size: 10pt;">Agility Robotics is deploying humanoid robots that are solving real-world challenges in logistics and manufacturing. Perceiving and understanding the world is critical to Digit’s success in these applications. The Perception team is looking for a staff machine learning engineer to own the design and development of object detection and tracking algorithms.</span></p> <p><span style="font-size: 12pt;"><strong>Responsibilities:</strong></span></p> <ul> <li style="font-size: 10pt;"><span style="font-size: 10pt;">As a Staff AI Engineer, you will own the architecture and technical roadmap for object perception systems used by the robot in production</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Design, develop, and deploy machine learning algorithms for multi-object detection, scene understanding, and 6-DoF object pose estimation</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Evaluate and drive adoption of state-of-the-art perception models</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Promote best practices in architecture, design, and testing to deliver high-quality, scalable software</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Optimize deep neural networks and associated data processing to run efficiently on embedded systems</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Collaborate with navigation, manipulation and hardware teams to align perception capabilities with product requirements</span></li> </ul> <p><span style="font-size: 12pt;"><strong>Requirements:</strong></span></p> <ul> <li style="font-size: 10pt;"><span style="font-size: 10pt;">5+ years of experience deploying machine learning-based object detection algorithms on mobile robots</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Master's or Ph.D. in Artificial Intelligence, Robotics, Computer Science, or a related discipline, with a strong foundation in machine learning, robotics, and intelligent systems</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Proficiency in related technical areas such as (but not limited to) deep convolutional neural networks, multi-object tracking, data association, supervised learning and pose estimation</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Strong mathematical fundamentals in linear algebra and numerical optimization and familiarity with core geometric concepts in computer vision</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Familiarity with common computer vision and machine learning libraries such as (but not limited to) PyTorch, OpenCV, NumPy, etc.</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Experience designing and optimizing algorithms for efficient execution across CPU and GPU architectures</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Experience with MLOps such as (but not limited to) data annotation services, data storage, model evaluation tools, and model deployment</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Publications in your field (CVPR, ICCV, RSS, ICRA preferred)</span></li> </ul> <p><span style="font-size: 12pt;"><strong>Bonus Qualifications:</strong></span></p> <ul> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Experience using YOLO, Faster/Mask R-CNN</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Experience developing ML models for 3 or 6 dof pose estimation</span></li> <li style="font-size: 10pt;"><span style="font-size: 10pt;">Experience in a technical leadership role</span></li> </ul> <p> </p> <p>This a hybrid position based out of one of our Salem, Pittsburgh, or Fremont offices.</p> <p><em>The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future.</em></p><div class="content-pay-transparency"><div class="pay-input"><div class="title">Anticipated Salary Range</div><div class="pay-range"><span>$207,000</span><span class="divider">—</span><span>$323,000 USD</span></div></div></div><div class="content-conclusion"><p><strong><em>In addition to base pay, our competitive total rewards package consists of the following for full-time employees:</em></strong></p> <ul> <li><strong>401(k) Plan:</strong><span class="Apple-converted-space"> </span>Includes a 6% company match.</li> <li><strong>Equity:</strong><span class="Apple-converte