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Salary
$150k – $250k per year
Location
In office (Irvine)
Visa
H-1B filings in 12 months: 37 · for this role: 31
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 30, 2026. First seen by Alion on Aug 12, 2025. FieldAI scores B on the Alion truth index.

Overview
Company
Impact
Profile match
FieldAI is a robotics company that builds embodied AI and autonomy software, marketed as a general-purpose robot brain, that lets mobile robots operate safely in unstructured real-world environments, headquartered in Irvine, California. Founded in 2023 by a team with backgrounds at NASA JPL, DeepMind, Tesla, NVIDIA and Amazon, it reports production deployments on three continents for customers in construction, energy, manufacturing, mining and federal markets. Its openings are mostly for robotics autonomy, perception and mapping engineers, machine learning and ML platform engineers, embedded, electrical and mechanical hardware engineers and infrastructure software roles.

Hardware Team:

The Hardware Team at Field AI develops perception and compute payloads that power autonomous robotics systems in complex real-world environments. Our work spans the full hardware stack designing and integrating sensing systems (LiDAR, camera, TOF, IMU, GPS), embedded compute (CPUs, GPUs, microcontrollers, ROS, sensor drivers), electrical systems (power distribution, communication), and mechanical components (structures, thermal regulation, ingress protection). The team focuses on both development (research, design, prototyping, testing) and operations (production, testing, QA, debugging). We’re a small, fast-moving team, and we care deeply about improving: 1) core capabilities, 2) system reliability, 3) system scalability. As a growing team we are also building operational systems and procedures from the ground up.

Sensor Systems Role:

As a Sensor Systems Engineer on the Hardware Team, you will contribute to the design, integration, calibration, and validation of the sensing systems that underpin our autonomy stack. You will work with a diverse array of sensors-LiDARs, depth cameras, IMUs, GPS, and more-ensuring each one delivers accurate, time-synchronized, and spatially consistent data in a range of environments and operating conditions. You will collaborate closely with the autonomy, compute, electrical, and mechanical teams to build tightly integrated solutions ready for deployment in challenging field environments. Additionally, while your focus will be on sensors you will likely contribute across all hardware domains.

What You Will Get To Do

1. Sensor System Design

  • Sensor Architecture: Work across hardware and software teams to define sensing requirements. Identity, test, and select sensors such as LiDARs, depth cameras, GPS, IMUs, ToF, and other devices.
  • Systems Integration: Integrate sensors with electrical (USB, Ethernet, I2C, CAN, GMSL), mechanical (mounts, jigs, isolation), and software (configurations, drivers, ROS nodes) systems. Ensuring power, thermal, and protocol compatibility.
  • Spatial Performance: Architect system to meet spatial sampling performance requirements including spatial coverage, range, resolution, and transform accuracy.
  • Temporal Performance: Implement and validate synchronization strategies, triggering schemes, timestamp encoding, and end-to-end latency minimization.

2. Sensor System Implementation

  • Performance Characterization: Evaluate sensor performance (spatial resolution, temporal drift, EMI noise, sync errors etc.). Test under real-world environmental conditions (vibration, lighting, moisture, temperature).
  • Calibration: Design and execute both intrinsic and extrinsic calibrations. Build alignment rigs and calibration boards as needed.
  • Optimization: Tune sensor configurations (exposure, gain, filtering, frame rate, etc.) and processing pipeline (filtering etc.) for optimal performance
  • Documentation: Create timing diagrams, sensor maps, coordinate transforms, and maintain all configuration files, launch scripts, driver references, and firmware states.

3. Sensor System Production & Servicing

  • Build: Work with vendors to procure sensors. Develop QA checks for incoming units. Support payload integration and manufacturing at scale.
  • Debug: Conduct root cause analysis of sensor systems including issues across hardware and software boundaries.
  • Monitor: Develop protocols for monitoring the sensing system health, data quality, and calibration status during field deployments.

What You Have

  • Education: B.S., M.S. or Ph.D. in Robotics, Electrical Engineering, Engineering Physics, Physics, or a related field.
  • Experience Level: We are recruiting across a wide range of experience levels from entry level engineers to senior and staff engineers.
  • Hands-On Sensors Experience: Hands-on work with perception sensors such as LiDAR, depth cameras, IMUs, GPS.
  • Systems Thinking: Cross-functional collaboration experience across electrical, mechanical, and software teams.
  • Sensor Physics: Strong foundation in optics, signal processing, and electromagnetic wave propagation.
  • Lab Skills: Hands-on testing, calibration, and debugging skills (oscilloscopes, logs, vibration/thermal setups)
  • Communication Protocols: Experience with protocols such as USB, Ethernet, GMSL, CAN, I2C, and CSI.
  • Computer & Software: Experience working with ROS/ROS2, sensor drivers, coordinate transforms (TF), and timing protocols (PTP, NTP, etc.).
  • Timing & Triggers: Experience with timestamping, synchronization, triggering, and latency constraints.
  • Calibration & Characterization: Experience designing and executing intrinsic, extrinsic, and temporal calibrations, along with sensor characterization under real-world environmental conditions.
  • Simulation: Experience high-fidelity simulation environments (Gazebo, Isaac Sim, RViz) for sensor modeling.

What Will Set You Apart

  • Scaling: Experience taking systems from prototype to large scale production.
  • Field Environments: Experience developing systems for harsh field environments.
  • Deployed Robotics: Experience working on robotics deployed in real world settings such as autonomous vehicles, drones, or ruggedized robots.
  • Systems Level Robotics: Fluency across software, electrical, and mechanical systems.
  • Autonomy Software: Knowledge of autonomy stacks used in robotics. As well as how sensor performance impacts autonomy algorithms.
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