Figure is a Bay Area robotics startup building AI-powered humanoid robots for industrial tasks such as warehouse and factory work.
<p>Figure is an AI Robotics company developing a general purpose humanoid. Our humanoid robot is designed for commercial tasks and the home. We are based in San Jose and require 5 days/week in-office collaboration. It’s time to build.</p> <p>We're looking for an Embedded Android Systems Engineer with deep expertise in low-level Android systems, the NDK, and real-time sensor and video pipelines. This is not a standard Android app role — you'll be building the mobile application that interfaces directly with our custom sensor hardware over USB, ingests high-frequency camera and IMU data in real time, and runs on-device AI inference at the edge.</p> <p>If you've spent time below the Java/Kotlin layer — writing C/C++ via the NDK, implementing custom HALs, or building zero-copy sensor pipelines — this role was built for you.</p> <p><strong>WHAT YOU'LL DO</strong></p> <ul> <li>Build and own the Android application that serves as the primary mobile interface to Figure's humanoid robots, connected via USB Host / Android Open Accessory protocols.</li> <li>Architect high-throughput, zero-drop data ingestion pipelines for high-FPS image sensors and high-frequency IMU data, using zero-copy memory techniques and real-time concurrency models.</li> <li>Implement custom hardware abstraction layers (HAL) and leverage the Android NDK (C/C++) for high-performance, low-latency processing.</li> <li>Optimize CPU/GPU workloads for real-time edge filtering under strict thermal and battery constraints, using foreground services and WorkManager for bulletproof background operation.</li> <li>Integrate on-device AI inference libraries (TFLite, MediaPipe, ONNX Runtime, OpenCV) for real-time computer vision and sensor fusion.</li> <li>Implement low-latency video streaming protocols (e.g. WebRTC) </li> </ul> <p><strong>WHAT WE'RE LOOKING FOR</strong></p> <ul> <li>Deep expertise in Android NDK (C/C++) — custom HAL development, USB Host/AOA protocol communication, and direct hardware interfacing below the standard SDK layer.</li> <li>Proven experience architecting real-time, low-latency data pipelines for high-bandwidth sensors — zero-copy memory, real-time concurrency, and synchronization with zero frame drops.</li> <li>Mastery of Android system resource management: CPU/GPU workload optimization, thermal and battery constraints, foreground services, and WorkManager.</li> <li>Strong proficiency in both C/C++ (NDK) and Kotlin/Java for Android.</li> <li>Experience shipping production Android applications in hardware-connected, latency-critical environments.</li> <li>Proven track record shipping and maintaining production Android applications at scale — including crash rate management, OTA update rollout strategies, real-time telemetry and monitoring pipelines, and sustaining reliability across a large, diverse active user base spanning multiple device configurations and Android OS versions</li> </ul> <p><strong>NICE TO HAVE</strong></p> <ul> <li>Experience integrating on-device CV/ML inference: TensorFlow Lite, MediaPipe, ONNX Runtime, or OpenCV applied to raw sensor feeds.</li> <li>Familiarity with WebRTC or other low-latency streaming protocols for real-time video.</li> <li>Background in DSP techniques applied directly to raw sensor data.</li> <li>Prior work in robotics companion apps, industrial Android devices, AR/computer vision mobile apps, automotive HMI, or drone control applications.</li> </ul> <p>The US <strong>base</strong> salary range for this full-time position is between $150,000 - $400,000 annually.</p> <p>The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.</p>