What you will be doingNeros builds autonomy for drones that operate in contested environments where GPS and communications are denied. The Autonomy Evaluation, Data & Test team owns how autonomy performance is measured across all Neros platforms: the regression and simulation infrastructure every software change is tested against, the data platform that ingests and indexes flight logs, the hardware-in-the-loop bench, and field test operations. As the leader of this team, you will define the metrics and acceptance criteria that determine whether autonomy software is cleared to fly, and build the team and systems that produce that evidence.
- Own the release criteria for autonomy software, including the definition of the regression gate, the conditions under which a build is blocked, and the process for reviewing exceptions
- Define autonomy performance metrics and their semantics for the organization, and publish coverage and reliability reporting to engineering and company leadership
- Build and operate a multi-tier regression system spanning unit and module tests, open-loop replay against logged flights, closed-loop simulation, and hardware-in-the-loop testing on production flight computers, including latency and deadline-miss measurement on target hardware
- Own the autonomy data platform end to end: on-vehicle capture, field egress, ingest and normalization, log catalog and query layer, deterministic replay at scale, and versioned dataset materialization for model training
- Direct field test and autonomy integration, including instrumented test articles, autonomy payload integration, range operations, log recovery, and flight-readiness execution
- Hire, lead, and develop a team of engineers spanning software infrastructure, data engineering, simulation, and physical test
You should have the following- 8+ years of engineering experience in robotics, autonomous vehicles, aerospace, or defense autonomy, including 3+ years managing engineers
- Direct experience leading an evaluation, validation, metrics, or test infrastructure function for a physical autonomous system
- Demonstrated experience defining performance metrics and acceptance criteria for autonomy or machine learning systems, and owning release gating decisions
- Hands-on experience building automated regression and CI infrastructure for robotics or autonomy software, in Python and C++
- Experience with large-scale log and sensor data infrastructure: ingest pipelines, time alignment across sensors, cataloging and query over multi-terabyte unstructured video and telemetry data, and deterministic replay
- Working knowledge of closed-loop simulation and hardware-in-the-loop testing, including real-time latency budgets and timing measurement on embedded compute
- Experience managing engineers across more than one discipline, including at least one outside your own technical background
- BS or MS in Computer Science, Robotics, Electrical Engineering, Aerospace Engineering, or a related field
Nice to Have- Experience building evaluation, simulation, or data infrastructure from the ground up at an autonomous vehicle, drone, or robotics company, rather than operating an established system
- Experience with machine learning data pipelines, including dataset versioning and lineage, labeling operations, and large-scale automated model evaluation
- Experience supporting or leading flight test and range operations, including instrumented test articles, test article turnaround, and flight-readiness review processes
- Background in guidance, navigation and control, multi-target tracking, sensor fusion, or electro-optical and infrared perception in maritime or air-to-air domains
US Salary Range$191,500 - $268,000 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.
