Mercor is seeking experienced Software and Firmware Engineers to support an advanced engineering and AI research initiative with a leading technology organization. We are looking for deeply hands-on engineers who have designed, implemented, integrated, tested, debugged, or validated software and firmware that directly interfaces with real-world hardware systems.
Relevant backgrounds include:
- Embedded Firmware Engineering
- FPGA / RTL Engineering
- Flight Software Engineering
- Hardware Test Automation Engineering
This role is particularly well suited for engineers who have worked directly on complex physical products and can bring practical engineering judgment to evaluating embedded systems, firmware, digital hardware, flight software, hardware-in-the-loop testing, and real-world debugging workflows.
Key Responsibilities
- Apply hands-on software, firmware, and digital hardware expertise to technically complex engineering tasks involving real physical systems.
- Review and evaluate embedded firmware, FPGA/RTL designs, flight software, test automation frameworks, hardware interfaces, and system-level engineering workflows.
- Analyze architecture and implementation trade-offs involving real-time performance, timing, memory, compute resources, interfaces, reliability, fault handling, concurrency, and hardware/software integration.
- Assess the technical correctness, robustness, and practical feasibility of engineering solutions for real-world embedded and hardware-connected systems.
- Identify implementation errors, incorrect assumptions, race conditions, timing issues, interface failures, resource constraints, and other system-level failure modes.
- Develop or review technically rigorous engineering problems, reference implementations, test cases, evaluation criteria, and supporting technical documentation.
- Draw on practical experience with development, integration, hardware bring-up, debugging, verification, validation, test automation, and deployment.
- Provide clear technical feedback grounded in real-world engineering experience and production hardware constraints.
You’re a Strong Fit If You Have
- 5+ years of professional software, firmware, FPGA, or embedded systems engineering experience, including at least 3 years of recent, actively hands-on experience developing, integrating, testing, bringing up, or troubleshooting software/firmware on real hardware—not solely program or people management.
- Demonstrated experience as the responsible engineer for production hardware-connected software or firmware, owning meaningful portions of the lifecycle from requirements and architecture through implementation, integration, hardware bring-up, verification, validation, debugging, and deployment.
- Deep technical expertise in at least one core domain: embedded firmware and real-time systems; FPGA/RTL design and verification; flight software and safety/mission-critical systems; or hardware test automation and hardware-in-the-loop infrastructure.
- Strong practical command of relevant technologies such as C/C++, Python, RTOS/bare-metal development, device drivers, bootloaders, embedded Linux, SPI/I²C/UART/CAN/Ethernet, Verilog/SystemVerilog/VHDL, FPGA toolchains, hardware interfaces, telemetry, and automated test systems, as applicable to the candidate's specialization.
- Extensive hands-on experience debugging software-hardware interactions and physical systems using tools such as JTAG/SWD debuggers, logic analyzers, oscilloscopes, hardware simulators/emulators, HIL/SIL environments, automated test equipment, CI infrastructure, and structured root-cause analysis.
- Proven experience developing systems in real-world product or hardware manufacturing environments, ideally across aerospace/defense, space, automotive/EV, semiconductors, consumer electronics, robotics/eVTOL, industrial/energy, or medical devices—e.g., Lockheed Martin, RTX, Boeing, Blue Origin, Rocket Lab, SpaceX, Tesla, Rivian, NVIDIA, Qualcomm, Intel, AMD, Apple, Google, Meta, Amazon, Skydio, Shield AI, Joby, Boston Dynamics, Siemens, ABB, Medtronic, or Intuitive Surgical—with the ability to clearly explain architectural decisions, implementation trade-offs, test results, and failure mechanisms.
Preferred Background
Experience working for a company that designs, builds, tests, and manufactures physical hardware or embedded systems is strongly preferred. Relevant organizations may include, but are not limited to:
- Aerospace & Defense: Lockheed Martin, Northrop Grumman, RTX, Boeing, General Atomics, L3Harris, BAE Systems, General Dynamics, Honeywell Aerospace, Textron
- Space: Blue Origin, Rocket Lab, Relativity Space, Firefly Aerospace, Sierra Space, Astranis, Planet, Maxar, Axiom Space
- Automotive & EV: Tesla, Rivian, General Motors, Ford, Lucid, Waymo, Zoox, Aptiv, Bosch
- Semiconductors: NVIDIA, Qualcomm, Intel, Analog Devices, Texas Instruments, Broadcom, Marvell, Micron, NXP, Infineon
- Consumer Electronics & Computing: Apple, Google Hardware, Meta Reality Labs, Microsoft Devices, Amazon, Samsung, Garmin, Sonos
- Drones, eVTOL & Robotics: Skydio, Shield AI, Zipline, Joby Aviation, Archer Aviation, Boston Dynamics, Figure, Agility Robotics, Wing
- Industrial, Energy & Medical Devices: Siemens, GE Aerospace, GE Vernova, ABB, Schneider Electric, Rockwell Automation, Enphase, Medtronic, Intuitive Surgical
Candidates from comparable hardware-focused organizations are equally encouraged to apply.
Why Join
- Apply your software and firmware expertise to technically challenging problems at the intersection of advanced hardware systems and AI research.
- Work on projects where practical experience with real hardware, embedded systems, FPGA/RTL, flight software, and test infrastructure is highly valued.
- Help improve how advanced AI systems reason about embedded development, hardware/software integration, digital design, real-time systems, testing, and debugging.
- Contribute remotely with flexible engagement structures alongside experienced engineers and researchers.
- Work on problems requiring genuine engineering judgment and production experience rather than purely theoretical software knowledge.