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Applied Intuition · 2 days ago

Machine Learning Engineer - Defense

Washington, DC

Full-time

Hybrid

Mid, Senior Level

$150K/yr - $225K/yr

5+ years exp

Applied Intuition is a vehicle intelligence company focused on the global adoption of safe, AI-driven machines. They are seeking a Machine Learning Engineer to develop, integrate, and maintain real-time AI/ML solutions for various autonomous vehicles, collaborating with teams to ensure seamless deployment in testing and demonstration events.

Artificial Intelligence (AI)Autonomous VehiclesEnterprise SoftwareInfrastructureSoftware

No H1B

Security Clearance Required

U.S. Citizen Only

Responsibilities

Develop, integrate, and adapt cutting-edge AI/ML algorithms running on the perception autonomy stack to process aerial imagery across a variety of platforms and sensor types (e.g. EO, IR)

Work with the best and most competitive AI talent in the world through collaboration with Applied Intuition commercial product staff

Scale up datasets using a variety of state-of-the-art data generation techniques including simulation, diffusion, and gaussian splats

Create inference software providing low-latency, real-time feedback to autonomy software on-board live platforms

Collaborate across the hardware, sensor, tracking, autonomy, and testing teams to ensure seamless deployment in on-site DoD testing and demonstration events

Leverage software-in-the-loop and hardware-in-the-loop testing and profiling to collect 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

Qualification

Machine LearningPyTorchC++AI algorithmsSensor physicsData generation techniquesMLOps pipelineRemote software developmentLarge datasets handlingLearning new softwareCollaboration

Required

MS or PhD in Computer Engineering, Robotic Engineering, Computer Science, or equivalent OR 5+ years of relevant experience working with simulation, machine learning, and ML infrastructure

Proficiency in training ML models in PyTorch on multi-machine, multi-GPU systems

Experience in optimizing and deploying machine learning models to edge devices

Strong Python knowledge and high capability in C++

A core understanding of sensor physics and sensor parameters

Experience leveraging modern AI-powered development tools (e.g., GitHub Copilot, Cursor) to accelerate the creation of robust, well-tested systems

Adeptness with remote software development, the ability to handle and process large datasets, and a capacity to learn new software and algorithms as needed with little supervision

Must be willing to travel as projects require, usually for SW/HW integration and/or demonstrations; estimated average travel is 2-5 days every other month (10-20%)

Must be a U.S. Citizen

Must hold or be eligible for a U.S. Secret security clearance

Preferred

PhD in Computer Vision, Machine Learning, or related field with strong academic contributions

5+ years of experience building and deploying perception models on real-world hardware

A background in generating datasets using simulation engines like Unreal Engine, NVIDIA Omniverse, or Blender

Experience with deeply optimizing Transformer-based models for edge devices like NVIDIA Jetson boards

Proficiency in modern C++ (2020, 2023), CMake, Conan

Familiarity with Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL), including integration and test experience on common COTS hardware devices (e.g., NVIDIA Jetson, Raspberry Pi5, M.2 accelerators)

Willingness to relocate to facilities near Destin, FL, Washington, D.C., or San Diego, CA