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Defense Perception Engineer (Computer Vision, Edge Deployment, and Data/ML Tooling)
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AI Summary
Build and deploy perception models for maritime, land, air-to-surface, and surface-to-surface domains in EO/IR. Develop custom detector/classifier architectures and supporting MLOps, labeling, and simulation tooling to iterate at scale. Requirements include MS/PhD or 5+ years experience in simulation and ML infrastructure, PyTorch multi-GPU training, and edge (Jetson) optimization with U.S. security clearance eligibility.
Key Highlights
Hands-on, full-stack, high-tempo work to push perception performance to second and third nine (99% / 99.9%) targets.
Deploy perception models to Jetson Orin+ and optimize for better-than-realtime FPS on Jetson-like hardware.
Own large-scale data and labeling workflows using in-house tools, simulation, and generative data generation techniques.
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Key Responsibilities
Develop perception models to find and classify targets with an error-rate objective of second and third nine (99% / 99.9%) performance.
Deploy perception models to Jetson Orin+ boards and optimize models for better-than-realtime performance.
Build foundation models to enable high-accuracy assisted data labeling.
Build tooling across the perception stack including labeling tools and simulation.
Scale up datasets using state-of-the-art data generation techniques including simulation, diffusion, and generative AI.
Create and maintain highly optimized models and inference software to deliver maximum attainable frames per second (FPS) on Jetson-like hardware.
Collaborate with hardware, sensor, tracking, autonomy, and testing teams to support seamless deployment in on-site DoD testing and demonstration events.
Technical Skills Required
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Benefits & Perks
Base salary, equity (options and/or restricted stock units), and benefits including health, dental, vision, life and disability insurance
401k retirement benefits with employer match
Learning and wellness stipends and paid time off
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Nice to Have
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
Background generating datasets using simulation engines like Unreal Engine, NVIDIA Omniverse, Blender, or 3D asset creation tools
Experience deeply optimizing Transformer-based models for edge devices like NVIDIA Jetson boards
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)
Job Description
Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co.
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