Helix AI Engineer, Android

Figure AI
San Jose, US
On-site

Who this role is best for

Best suited to mid-level Android engineers with expertise in low-level systems and real-time sensor pipelines working in robotics or hardware-connected environments.

Best fit for

  • Engineers who have worked below the Java/Kotlin layer in Android systems.
    — “If you've spent time below the Java/Kotlin layer
  • Candidates with experience in high-throughput, zero-drop data ingestion pipelines.
    — “Architect high-throughput, zero-drop data ingestion pipelines
  • Developers proficient in both C/C++ (NDK) and Kotlin/Java for Android.
    — “Strong proficiency in both C/C++ (NDK) and Kotlin/Java for Android

Things to consider

  • Requires 5 days per week in-office collaboration in San Jose.
    — “require 5 days/week in-office collaboration
  • Role involves strict thermal and battery constraints for optimization.
    — “strict thermal and battery constraints

How to stand out

  • Highlight specific projects involving custom HAL development and USB Host/AOA protocols.
    — “custom HAL development, USB Host/AOA protocol communication
  • Showcase experience with on-device AI inference libraries like TFLite or MediaPipe.
    — “Integrate on-device AI inference libraries (TFLite, MediaPipe, ONNX Runtime, OpenCV)
  • Demonstrate a track record of shipping production Android applications in hardware-connected environments.
    — “Experience shipping production Android applications in hardware-connected, latency-critical environments
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · TeamLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Built and owned the Android application that interfaces directly with custom sensor hardware
  • Optimized CPU/GPU workloads for real-time edge filtering
Typical background
Deep expertise in Android NDK (C/C++)Proven experience architecting real-time, low-latency data pipelines

Skills & requirements

Required

C/c++Android NDKUSB Host/aoa ProtocolReal-time ConcurrencyZero-copy MemoryAndroid System Resource ManagementKotlin/java

Preferred

Tensorflow LiteMediapipeONNX RuntimeOpencvWebrtc

Stack & domain

Android NdkCustom Hal DevelopmentUsb Host/aoa Protocol CommunicationDirect Hardware InterfacingReal-time Sensor And Video PipelinesZero-copy Memory TechniquesReal-time Concurrency ModelsOn-device Ai Inference LibrariesLow-latency Video Streaming ProtocolsWebrtcTfliteMediapipeOnnx RuntimeOpencvForeground ServicesWorkmanagerThermal And Battery ConstraintsCpu/gpu Workload OptimizationReal-time Telemetry And Monitoring PipelinesSustaining ReliabilityProduction Android ApplicationsCrash Rate ManagementOta Update Rollout StrategiesTeam CollaborationProject ManagementProblem-solvingInnovationAdaptabilityAttention To DetailCustomer SatisfactionAndroid Application DevelopmentSensor Data ProcessingAi InferenceVideo StreamingReal-time SystemsMobile RoboticsHumanoid RobotsSensor FusionComputer Vision

About the role

Original posting from Figure AI via Greenhouse

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.

We're looking for a Senior Android 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.

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.

WHAT YOU'LL DO

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.

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.

Implement custom hardware abstraction layers (HAL) and leverage the Android NDK (C/C++) for high-performance, low-latency processing.

Optimize CPU/GPU workloads for real-time edge filtering under strict thermal and battery constraints, using foreground services and WorkManager for bulletproof background operation.

Integrate on-device AI inference libraries (TFLite, MediaPipe, ONNX Runtime, OpenCV) for real-time computer vision and sensor fusion.

Implement low-latency video streaming protocols (e.g. WebRTC) 

WHAT WE'RE LOOKING FOR

Deep expertise in Android NDK (C/C++) — custom HAL development, USB Host/AOA protocol communication, and direct hardware interfacing below the standard SDK layer.

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.

Mastery of Android system resource management: CPU/GPU workload optimization, thermal and battery constraints, foreground services, and WorkManager.

Strong proficiency in both C/C++ (NDK) and Kotlin/Java for Android.

Experience shipping production Android applications in hardware-connected, latency-critical environments.

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

NICE TO HAVE

Experience integrating on-device CV/ML inference: TensorFlow Lite, MediaPipe, ONNX Runtime, or OpenCV applied to raw sensor feeds.

Familiarity with WebRTC or other low-latency streaming protocols for real-time video.

Background in DSP techniques applied directly to raw sensor data.

Prior work in robotics companion apps, industrial Android devices, AR/computer vision mobile apps, automotive HMI, or drone control applications.

The US base salary range for this full-time position is between $150,000 - $400,000 annually.

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.

Source: Figure AI careers (Greenhouse)

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