Perception Engineer - Defense Autonomy

Perception Engineer - Defense Autonomy

As a Perception Autonomy engineer at EpiSci, you will be pivotal in developing, integrating, and maintaining real-time sensor software solutions deployed across a range of heterogenous autonomous vehicles and different domains (e.g., land, air, sea, and space). You will work with a team to continuously add capability and demonstrate the solution to customers in real-world scenarios on a variety of hardware platforms. Your responsibility will primarily be designing, developing, and rapidly integrating AI/ML sensor algorithms to interface across different platforms, ingest relevant mission information, and support the autonomy team's mission objectives. This work includes developing autonomous sensor controllers to optimally fuse information between state-of-the-art sensor systems, such as EO, IR, acoustics, radar, and RF.

At EpiSci, you will:

• Develop, integrate, and adapt cutting-edge AI/ML algorithms running on the perception autonomy stack to collect relevant information across a suite of platform sensors
• Create interfacing software to autonomously control sensors (e.g., EO, IR, acoustics, radar, and RF)
• Collaborate across the sensor, tracking, and autonomy teams to ensure seamless deployment of heterogenous platform swarms in on-site DoD testing and demonstration events
• Deploy containerized autonomy solutions to embedded Linux devices, leveraging computer-in-the-loop testing and profiling, and efficiently collecting performance data
• Interact with the DoD customer to understand their use cases, requirements, and triage needs during field events to deliver a superior customer experience
• Work closely with our existing team to internally triage technical problems and scope
• Carefully communicate and document ongoing work to ensure internal flexibility in a fast paced environment as well as clarify progress with external customers
• Drive execution of simulation tooling to playback sensors, platforms, and autonomy in post processing field test analysis
• Implement improvement plans for future integration efforts based on simulation analysis and customer feedback

We're looking for someone who has:

• MS or PhD in Electrical Engineering, Computer Engineering, Robotic Engineering, Computer Science, Optimization, or equivalent OR 5+ years of relevant experience working with sensor algorithms, hardware, and HIL software integration
• Experience with multiple sensor modalities (e.g., EO, IR, lidar, radar, sonar, acoustics, etc.)
• Core understanding of sensor physics and sensor control parameters
• Experience training and deploying ML algorithms (python, pytorch, tensorflow) onto integrated systems (onnx, C++ models)
• Familiarity with tracking basics (e.g., Kalman filters) and optimal sensor fusion
• Experience working comfortably in Windows, Linux, and Docker
• Prior experience with remote software development, ability to handle and process large datasets, and learn new software and algorithms as needed with little supervision

Travel Requirements:

• Must be willing to travel as projects require, usually for SW/HW integration and/or demonstrations; estimated average travel is every 1-2 months for 2-5 days (10-20%)
• Travel-adverse candidates are encouraged to inquire about relocation assistance to HQ in Poway, CA

Security Requirements:

• Must be a U.S. Citizen
• Must hold or be eligible to obtain and maintain a U.S. security clearance

Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment.

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the location listed is: $140,000 to $220,000 USD annually.