Senior Embedded Engineer

About the Role

Uber is launching AV Labs to accelerate the autonomous technology ecosystem. We're building out a high-velocity team of multi-disciplinary experts to turn real-world operations into high-quality data for our autonomous partners. This team is focused on the hardest problem in AV today: unlocking real-world, long-tail driving data. Autonomy is now a data race—and Uber has an edge: We collect rare, real-world driving data at a scale and capital efficiency no one else can match.

Our AV Labs Hardware team is pioneering the next-generation E/E architecture for our cutting-edge L4 data collectioncapable vehicle fleet.You will drive critical projects ranging from initial 3rd-party hardware driver and firmware development to the embedded development, bring-up, and deployment of our in-house designed production hardware. As a Senior Embedded Engineer, your technical expertise will directly accelerate our path to production, playing a key role in shaping the reliability of our autonomous data collection fleet.

What the Candidate Will Do

Develop Core Firmware & Drivers: Design, write, and maintain robust firmware and low-level device drivers for 3rd-party automotive-grade components and critical AV sensors (LiDAR, radar, cameras) to enable immediate, high-fidelity data collection and shadow mode operations.

Drive In-House Hardware Bring-Up: Execute the transition to production by taking ownership of board bring-up, hardware validation, and low-level software deployment for our custom, in-house designed autonomous computing platforms.

Collaborate on HW/SW Co-Design: Partner closely with electrical and hardware engineering teams to implement hardware-software interfaces, participate in schematic reviews, and ensure component selection aligns with firmware requirements.

Debug & Optimize Complex Systems: Utilize hardware debugging tools (oscilloscopes, logic analyzers) and software profiling to troubleshoot intricate system-level issues, optimize sensor data pipelines, and ensure strict timing and network synchronization across the vehicle.

Contribute to Team Excellence: Act as a technical resource and mentor within the hardware team, actively contributing to best practices for embedded software architecture, code quality, and scalable deployment.

Basic Qualifications

Embedded Software Experience: Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, accompanied by 5+ years of professional experience developing embedded software using modern C/C++ in RTOS (e.g., FreeRTOS, Embedded Linux) or bare-metal environments.

Low-Level Driver & Automotive Hardware Expertise: Strong experience writing firmware and device drivers for complex, automotive-grade components, SoCs, and autonomous vehicle sensors (e.g., LiDAR, radar, cameras). This must include hands-on experience with sensor integration, board bring-up, hardware debugging tools (e.g., oscilloscopes, logic analyzers), and familiarity with standard automotive interfaces and vehicle networks (e.g., CAN/CAN-FD, Automotive Ethernet, FPD-Link/GMSL, PCIe, SPI, I2C).

Production Lifecycle Execution: Demonstrated experience contributing to embedded hardware systems from initial prototyping and 3rd-party integration through to production deployment—ideally within the autonomous vehicle, robotics, or mission-critical automotive domains.

Preferred Qualifications

Hardware-Software Co-Design: Experience collaborating closely with electrical and hardware engineers on custom board designs, including participation in schematic reviews and component selection for computing platforms.

Functional Safety & Automotive Standards: Understanding of automotive functional safety standards and their application in embedded software development, including experience with ISO 26262 (ASIL B through ASIL D) compliance and adherence to coding guidelines like MISRA C/C++.

Advanced Timing & Synchronization: Experience with distributed system timing and hardware synchronization methodologies critical for sensor fusion. Familiarity with Precision Time Protocol (PTP/gPTP, IEEE 802.1AS) and hardware PPS routing across complex vehicle networks is highly valued.

High-Performance AV Compute Platforms: Experience developing firmware and drivers for modern, high-performance autonomous driving SoCs and compute platforms (e.g., NVIDIA DRIVE, Qualcomm Snapdragon Ride) and optimizing data pipelines utilizing hardware accelerators (GPUs, DSPs, NPUs).