Embedded Systems Engineer-Federal

FieldAI•Pittsburgh, PA

2d•Onsite

About The Position

Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications. Learn more at https://fieldai.com. About the Job At FieldAI , we build autonomous robotic systems that operate in demanding, real-world environments where tight integration between hardware and software is critical. We’re looking for an Embedded Systems Engineer to support design, implementation, integration, and , deployment of wheeled robotic platforms across both federal and commercial programs Embedded Systems Role: As an Embedded Systems Engineer on the Federal Team at Field AI, you will contribute to the architecture, configuration, and validation of the compute systems that serve as the backbone for our robotic platforms. Your work will span low-level firmware, Linux-based configuration, and system performance analysis across ARM and x86 SBC platforms. From firmware on microcontrollers to ROS data streams on SBCs, you’ll ensure the entire compute stack is optimized, reliable, and robust under field conditions. You will collaborate closely with the sensor, electrical, and autonomy teams to build tightly integrated solutions ready for deployment in challenging field environments. Additionally, while your focus will be on computing systems you will likely contribute across all hardware domains.

Requirements

B.S., M.S., or Ph.D. in Computer Engineering, Robotics, Electrical Engineering, or a related field.
Experience with embedded platforms (Jetson, Raspberry Pi, x86 NUCs, custom SBCs).
Proficiency with Linux system configuration, scripting, and headless deployment tools.
Strong skills in firmware development for microcontrollers, including bare-metal and RTOS environments.
Proficient in C++ and Python for embedded and application-level development.
Experience with USB, Ethernet, I²C, SPI, CAN, GMSL, and similar interfaces.
Familiarity with ROS, device drivers, TF, and data streaming/publishing.
Comfort with hardware/software debugging tools (oscilloscopes, logs, power monitors, analyzers).
Ability to diagnose and optimize across compute, thermal, timing, and I/O layers.
U.S. Person eligibility required for the FieldAI Federal Team, which works on projects connected to the U.S. government. A U.S. Person as defined by 22 C.F.R §120.62 includes U.S. Citizen, U.S. National, lawful permanent residents (green card holders) refugee or asylee.

Nice To Haves

Experience taking systems from prototype to large scale production.
Experience developing systems for harsh field environments.
Experience working on robotics deployed in real world settings such as autonomous vehicles, drones, or ruggedized robots.
Fluency across software, electrical, and mechanical systems.
Knowledge of autonomy stacks used in robotics. As well as how compute performance impacts autonomy algorithms.

Responsibilities

Architect and configure embedded compute platforms (ARM/x86, SBCs) for robotic applications including evaluation, testing and selection.
Set up and customize Linux environments (Ubuntu, Yocto, JetPack), middleware (ROS), and I/O interfaces.
Integrate compute with sensing and robotic systems. Analyze thermal, power, and bandwidth constraints to meet deployment and runtime requirements.
Bring up sensors and peripherals using a range of protocols (USB, Ethernet, GMSL, I²C, SPI, CAN).
Build and maintain drivers, ROS nodes, and data acquisition pipelines for new hardware components.
Create configuration files, launch scripts, and firmware update workflows.
Conduct system-level tests such as thermal profiling, latency measurement, and power draw analysis.
Maintain flashing procedures, I/O maps, and debug kits. Manage compute and I/O budgets.
Work with vendors to procure compute hardware. Develop QA checks for incoming units. Support payload integration and scaling.
Support root-cause analysis for boot, connectivity, and throughput issues.
Implement watchdogs, health checks, and other evaluation tools. Monitor compute system performance across CPU, GPU, memory, I/O, and networking.