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Heven AeroTech

Hydrogen-powered UAVs for long-endurance, multi-mission

Senior Machine Learning Engineer - Autonomy

Robotics & Autonomous SystemsConfirmed live in the last 24 hours
Full-timeBingen, WA, USA$150k - $172k

About the Job

Requirements

  • A BA/BS degree in Computer Science, Electrical Engineering, Robotics, Aerospace Engineering, or a related technical field, or equivalent practical experience.
  • At least five years of relevant engineering experience in autonomy, robotics, machine learning, or related embedded software systems, including hands-on development and deployment of machine learning or autonomy capabilities on physical platforms.
  • Ability to independently lead a significant technical effort from requirements and design through implementation, integration, and testing.
  • Strong hands-on C++ and Python development skills, including Linux-based development, debugging, profiling, and modern machine learning frameworks.
  • Substantial experience in one or more of perception, tracking, sensor fusion, autonomous decision making, or planning, with the ability to integrate these capabilities into a complete vehicle system.
  • Experience defining software architecture and system interfaces, making technical tradeoffs, and resolving integration problems across software and hardware.
  • Experience deploying and optimizing software or machine learning models on resource-constrained onboard compute.
  • Experience developing repeatable tests, evaluating performance against defined requirements, and investigating failures using system logs and test data.
  • Ability to provide technical guidance, review designs and code, and mentor other engineers.
  • Ability to work on-site in Bingen, Washington, and support hands-on aircraft integration, ground test, and flight test activities.
  • Professional working proficiency in spoken and written English.
  • Familiarity with autopilot and ground control station ecosystems such as Applied Navigation Quattro/QET, ArduPilot, and PX4, or similar.
  • Experience serving as test conductor or safety officer for field test operations.
  • Exposure to GNSS performance evaluation, including degraded or contested environments.
  • Exposure to automated or vision-based landing evaluation.
  • Experience with modeling and simulation tools relevant to vehicle performance and dynamics, such as six-degree-of-freedom simulation, vortex lattice methods, computational fluid dynamics, or finite element analysis.
  • Familiarity with requirements traceability and verification and validation practices.
  • Familiarity with ADS-B, detect-and-avoid, and airspace integration considerations for uncrewed systems testing.
  • Experience with test instrumentation design and integration on space- and weight-constrained platforms.
  • FAA Part 107 certification or equivalent operational credentials.
  • Experience working in multidisciplinary engineering teams in a rapid development environment.
  • Not eligible for visa sponsorship; applicants must be legally authorized to work in the United States without employer sponsorship, now or in the future.
  • If the role requires access to information controlled under U.S. export control laws (ITAR/EAR), applicants must qualify as a U.S. person under 22 CFR §120.62, such as a U.S. citizen, U.S. national, lawful permanent resident, or protected individual such as an asylee or refugee.
  • Willingness and ability to perform field work, including standing and walking for extended periods, carrying equipment, and working outdoors in varying conditions.
  • Willingness to travel as needed for test events.
  • Ability to support flexible hours based on test schedules.

Responsibilities

  • Own technical execution of assigned autonomy capabilities, including requirements development, architecture, implementation, integration, verification, and delivery.
  • Translate mission needs into defined autonomous behaviors, operating constraints, measurable performance requirements, and test acceptance criteria.
  • Make and document technical tradeoffs across machine learning, deterministic logic, state machines, behavior trees, planners, and optimization methods based on mission needs, system constraints, and test evidence.
  • Design and implement mission-level autonomous behaviors, including mission execution, replanning, contingency handling, and coordination with operator commands and aircraft operating limits.
  • Lead development and integration of perception capabilities, including object detection, classification, tracking, scene understanding, sensor fusion, and geospatial reasoning.
  • Define and maintain interfaces between autonomy software, autopilots, companion and mission computers, sensors, payloads, data links, and GCS/C2 systems, including clear boundaries between mission autonomy and flight-control authority.
  • Develop and review production-quality C++ and Python software for real-time and near-real-time execution; evaluate and optimize latency, throughput, memory use, and compute utilization on NVIDIA GPU and embedded platforms.
  • Own the model development and deployment process for assigned capabilities, including dataset quality, training and evaluation methods, regression testing, versioning, deployment, and rollback.
  • Define behavior for degraded sensors, uncertain perception outputs, compute limitations, and interrupted communications, including fallback behavior and operator intervention.
  • Develop verification strategies using simulation, software-in-the-loop, hardware-in-the-loop, bench testing, and automated testing to evaluate nominal, degraded, and failure conditions before flight.
  • Lead autonomy software integration and troubleshooting during ground and flight test; analyze logs and test data, identify root causes, and drive corrective actions through verification.
  • Break complex efforts into achievable milestones, identify technical risks and dependencies, and communicate progress and tradeoffs to engineering leadership.
  • Mentor junior and mid-level Machine Learning Engineers through hands-on development, design and code reviews, debugging, and test planning, helping them build technical judgment and take on increasing responsibility for deployed capabilities.
  • Coordinate technical work across Machine Learning, Platform Engineering, Flight Test, avionics, electrical, mechanical, and other engineering teams.
  • Perform other duties as assigned.

Desired Qualifications

  • Direct experience delivering UAS autonomy capabilities through aircraft integration and flight test.
  • Experience with NVIDIA embedded platforms, CUDA, TensorRT, ROS 2, MAVLink, or comparable robotics and vehicle interfaces.
  • Experience with EO and IR perception, target tracking, geolocation, or navigation under degraded sensor conditions.
  • Experience with software-in-the-loop and hardware-in-the-loop environments, scenario-based testing, and regression testing of autonomous behaviors.
  • Experience with model quantization, hardware-accelerated inference, and maintaining model performance across changes in sensors or operating conditions.
  • Experience integrating autonomy with operator workflows, mission planning, and GCS/C2 systems.
  • Aerospace or defense experience and eligibility to obtain a DoD Secret clearance.

About the Company

Heven AeroTech

Hydrogen-powered UAVs for long-endurance, multi-mission

Heven AeroTech makes hydrogen-powered unmanned aerial vehicles (UAVs) for defense, industrial, and public-safety uses, emphasizing long endurance and heavy payloads. Its lineup includes the H2D55 multi-rotor, H2D200/250 fixed-wing hybrids, the H100 octocopter for cargo and emergencies, and the Raider long-range VTOL drone, all designed for extended missions. Hydrogen propulsion provides longer flight time with a near-zero acoustic signature, complemented by autonomous flight control, real-time telemetry, rapid refueling, and modular payload bays. The company differentiates itself with hydrogen power, higher endurance and payload capacity, quiet operation for covert work, and regional manufacturing partnerships in the U.S. and India to enable local assembly and global deployments, aiming for sustainable, long-range aerial mobility for ISR, security patrols, remote delivery, and industrial monitoring.

Company size
51-200
Company stage
Series B
Total funding
$100M
Headquarters
Haifa, Israel
Founded
2019

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