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Applied Perception Engineering Lead

Applied Intuition
San Diego, California, United States$175k – $235kPosted 4 May 2026

Job Description

About Applied Intuition 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 . We are an in-office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. About the Role We are looking for a Perception Team Lead who will lead a team in developing Perception pipelines for multiple modalities (EO/IR, Radar, with growth paths into Acoustics, Passive RF, and Sonar). The software will be deployed in the real world for government and defense applications. This position will help the team execute effectively through technical guidance, mentoring, collaboration with other peer teams, integration into broader systems, and using best practices for designing and building software systems. You will be responsible for maintaining and executing the technical roadmap for the Perception pipelines as well as a Perception Autonomy service, which is responsible for a number of perception-related behaviors (e.g., camera scanning, slew and cue, object following, dynamic EMCON modes, multi-track custody, track handoff between sensors, etc.). Please note that this role does not include training ML models; instead, it will be responsible for integrating pre-trained models into these pipelines. At Applied, you will: Manage a team of talented software engineers working together on exciting perception and perception autonomy projects. Oversee and contribute to the development of perception pipelines utilizing EO/IR and Radar sensor modalities, with potential of moving into perception pipelines for Acoustics, Passive RF, and Sonar sensors. Oversee and contribute to the Perception Autonomy service, which includes a growing number of behaviors, such as camera scanning, slew and cue, object following, dynamic EMCON modes, multi-track custody, and track handoff between sensors. Lead the development and incorporation of pre-trained models (produced by a separate team) into production Perception pipelines. Ensure your team delivers high quality, robust software that can fulfill project requirements for real-world deployment on hardware components. Work closely with partners and internal teams to ensure success on project milestones, and seamless integration with peer teams platforms. Manage and track multiple priorities while maintaining a focus towards common project goals. We're looking for someone who has: MS in computer science, ML, robotics, or related fields from a top institution. 8+ years industry experience in Perception-related fields (e.g., ATR, ML). 2+ years experience in leading teams with varied backgrounds. Experience with deploying software to hardware components with rigorous verification and validation. Experience with perception pipelines using real-time data from Radar and EO/IR systems. Deep technical understanding of production-level development in C++ and/or Python for integrating object de ... (truncated, view full listing at source)
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