Job description

Who we are Neros is a defense technology company rebuilding America’s drone industrial base. We design and manufacture high-performance unmanned systems that are tested in combat, iterated at startup speed, and built at massive scale. Our team culture is fast, hands-on, and obsessed with closing the gap between design and deployment. As drones transform the character of warfare, Neros is delivering the systems the West needs to compete on the modern battlefield and deter the adversaries of democracy. We’re hiring engineers, operators, and builders who want to move fast, take on extreme ownership, and get capability into the hands of warfighters in months, not years. What you will be doing The Autonomy Platform Lead owns the onboard software platform on which all Neros autonomy software runs, spanning the runtime architecture and module interfaces, real time scheduling and latency accounting, on vehicle logging and time synchronization, and the build, release and deployment path onto the aircraft. This role leads a small platform engineering team while contributing directly to the software, and is accountable for maintaining a single configurable runtime across all Neros unmanned aircraft rather than per program forks. The Autonomy Platform Lead additionally represents autonomy in hardware co-design, carrying the compute, power, thermal and mass requirements of the autonomy payload into bill of materials decisions, and owns deployment of the autonomy software stack onto the selected embedded compute. Responsibilities Own the architecture, roadmap and delivery of the autonomy runtime, including the module interface contract, process and thread model, message passing, execution rates and latency guarantees that every other autonomy group develops against Maintain a single autonomy runtime across all vehicle platforms through a platform configuration layer, such that a new airframe revision is delivered as a configuration change rather than a software fork, and enforce that boundary against per program divergence Own real time scheduling, latency accounting and deadline monitoring, including end to end sensor to actuator measurement on flight hardware under sustained thermal load, and deliver the instrumentation required for latency to be enforced as a release gate Own build, release, versioning and deployment of autonomy software to bench and field vehicles, the autonomy continuous integration infrastructure jointly with the evaluation organization, and on vehicle logging and hardware time-stamping, including full rate capture with triggered dump, time synchronization across sensor, compute and flight controller, and log integrity, without degrading control loop performance Own the representation of autonomy in hardware co-design and bill of materials decisions by quantifying compute, power, thermal and mass requirements against measured latency budgets, and own deployment of learned components to the selected embedded accelerator, including quantization and characterization of the resulting accuracy and latency trade off Lead and grow the platform engineering team through hiring, mentorship and technical review, while continuing to contribute directly to the codebase as an engineer You should have the following 5+ years of professional experience developing production embedded, robotics or real time software, including 2+ years leading an engineering team or a technical program as a tech lead or engineering manager, with continued hands on technical contribution throughout Demonstrated delivery of software onto a physical vehicle or embedded platform operating outside a laboratory, such as unmanned aircraft, ground or aerial robotics, autonomous vehicles, automotive or aerospace systems, including responsibility through bring up, integration and field operation rather than simulation or research alone Expert proficiency in modern C++ on embedded Linux, and working proficiency in Python for tooling and automation, developed under real time and resource constrained requirements Ownership of the architecture of a robotics or vehicle software runtime or middleware layer, covering the process and thread model, inter process communication and message passing, module interface definition, and execution scheduling, using ROS 2, DDS, Zenoh, LCM, or a proprietary equivalent Depth in real time systems engineering, including scheduling policies and priorities, CPU affinity and isolation, lock free or zero copy data paths, jitter and deadline analysis, and measurement of end to end latency distributions on target hardware rather than in simulation Experience implementing time synchronization and hardware time-stamping across sensors, compute and a flight or vehicle controller, using PTP or gPTP, PPS, sensor trigger lines, or equivalent, and reconciling multiple clock domains in logged data Ownership of build, release and continuous integration for embedded targets, including cross compilation and toolchain management, Yocto, Buildroot or containerized build environments, versioned and reproducible artifacts, and over the air or field software update Experience building high rate on vehicle data logging, including ring buffer and triggered capture, multi sensor and video streams, storage and bandwidth budgeting, and log integrity, delivered without degrading control loop timing Experience deploying neural networks to embedded accelerators such as NVIDIA Jetson and TensorRT, Qualcomm QNN or SNPE, Texas Instruments TIDL, Hailo, or equivalent, including quantization and characterization of the resulting accuracy and latency trade off Experience working directly with hardware and electrical engineering teams to specify compute, memory, power, thermal and mass requirements for an embedded compute payload, including system on module or carrier board selection and participation in bill of materials decisions Nice to Have Unmanned aircraft experience specifically, including integration between an onboard mission computer and a flight controller or autopilot, using PX4, ArduPilot and MAVLink or a proprietary equivalent, and familiarity with the flight modes, arming logic and failsafe behavior at that boundary Design and build of hardware in the loop benches, including sensor simulation and injection, hardware timestamp instrumentation, and integration of a HIL bench into automated release gating Experience carrying a software platform through transition to volume manufacturing, including per unit calibration data management, provisioning at the factory, and staged software update across a large deployed fleet US Salary Range $201,000 – $281,000 USD The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are considered part of Neros' total compensation package. We’re an equal opportunity employer. We welcome all applicants without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

Requirements

Must-haves

Lead and grow the platform engineering team through hiring, mentorship and technical review, while continuing to contribute directly to the codebase as an engineer
You should have the following
Expert proficiency in modern C++ on embedded Linux, and working proficiency in Python for tooling and automation, developed under real time and resource constrained requirements
We’re an equal opportunity employer. We welcome all applicants without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

Nice-to-haves

Design and build of hardware in the loop benches, including sensor simulation and injection, hardware timestamp instrumentation, and integration of a HIL bench into automated release gating
Experience carrying a software platform through transition to volume manufacturing, including per unit calibration data management, provisioning at the factory, and staged software update across a large deployed fleet

Application prep

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Keywords to mirror

python

Platform: greenhouse
Effort: quick

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