Description

Heven AeroTech is hiring a Senior Machine Learning Engineer, Autonomy to own the development and delivery of machine learning and autonomy capabilities for uncrewed aircraft systems. The role covers perception, tracking, sensor fusion, mission-level decision making, planning, software architecture, integration, verification, ground and flight testing, and technical mentorship. It is an on-site position in Bingen, Washington, requires five or more years of relevant autonomy or embedded software experience, and offers a salary range of $150,000 to $172,000 USD.

Required Skills

C++
Python
Sensor fusion
Autonomy
NVIDIA GPU
ROS 2
CUDA
TensorRT
MAVLink

Additional Information

Minimum Education: Bachelor of Arts or Bachelor of Science degree in Computer Science, Electrical Engineering, Robotics, Aerospace Engineering, or a related technical field, or equivalent practical experience.
Required Previous Experiences: 5+ years of relevant engineering experience in autonomy, robotics, machine learning, or related embedded software systems, including hands-on development and deployment on physical platforms.
Experience independently leading significant technical efforts from requirements and design through implementation, integration, and testing.
Substantial experience in 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.
Experience providing technical guidance, reviewing designs and code, and mentoring other engineers.
Experience serving as a test conductor or safety officer for field test operations.
Exposure to GNSS performance evaluation in degraded or contested environments.
Exposure to automated or vision-based landing evaluation.
Experience with vehicle performance and dynamics modeling and simulation tools.
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.
Preferred 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 SIL/HIL 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.
Translation Company Name: Heven AeroTech

About Heven AeroTech

Heven AeroTech

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Sr. Machine Learning Engineer, Autonomy at Heven AeroTech

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