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 applied.co. We are an in-office company, and our expectation is that full-time 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. This in-office expectation does not apply to contractor positions ABOUT THE ROLE Applied Intuition builds the software infrastructure for autonomous vehicles across passenger cars, trucking, mining, and defense. Our Self-Driving Systems (SDS) team develops production-grade autonomy stacks deployed on real vehicles across multiple continents, from highway trucking in Japan to urban ADAS in the United States and Europe. We are looking for a Technical Lead Manager to own the perception model at the core of our autonomy stack. This is a single combined model: shared backbone, multi-task heads, serving every SDS program from the same codebase. The same model runs on a passenger car in Los Angeles, a truck in rural Japan, and an offroad vehicle in the Philippines. Different sensor configurations, different road geometries, different weather distributions, one model. You will lead the team that trains, evaluates, and ships this model, and you will be hands-on in the architecture and training decisions that drive its performance. AT APPLIED INTUITION, YOU WILL: - Own the perception model end-to-end: architecture, training, evaluation, and deployment. The core challenge is building a model that generalizes across geographies, road types, sensor setups, and environmental conditions without per-vertical forks. - Drive a camera-first perception strategy. The goal is to progressively reduce dependencies on HD maps and lidar. How to get there is part of the job. - Lead training and iteration cycles hands-on. You will be in the data, the eval dashboards, and the failure analysis. When perception regresses in a new geography or road type, you own understanding why and fixing it. - Own model performance across the full deployment surface: highway, urban, residential, ramps, complex intersections, poor weather, hilly terrain. You care about on-vehicle driving outcomes, not just offline metrics. - Manage the model lifecycle from training through quantization and deployment on embedded compute, including device-specific optimizations. Close the gap between what the model does offboard and what it does on the vehicle. - Work directly with OEM customer programs to understand sensor configurations, target ODDs, and performance requirements. Translate these into model architecture and data strategy. - Recruit, develop, and technically lead a team of perception engineers. Set high technical standards and create a culture of rigorous experimentation and measurement. WE’RE LOOKING FOR SOMEONE WHO HAS: - Bachelors degree in any field, or equivalent combination of education and work experience. - 5+ years in ML/deep learning for perception or 3D scene understanding. Deep hands-on experience training and deploying vision models at scale. - 2+ years managing a perception team, with ability to both set direction and contribute to architecture and training decisions directly. - Experience building production perception systems, especially camera-only or camera-first solutions. - Track record deploying perception models to embedded hardware under real-time latency and compute constraints, including device-specific optimizations. - Strong software engineering in Python and C++, comfortable across the stack from training code to onboard inference integration. - Experience scaling perception models across multiple geographies, sensor setups, or vehicle platforms. NICE TO HAVE: - Deep familiarity with transformer-based architectures for 3D perception, BEV representations, multi-task learning, and dense prediction. - Familiarity with occupancy-based scene representations, sparse query-based architectures, or temporal aggregation approaches. - Experience reducing or removing map dependencies in perception systems. - Background in autolabel pipelines, data quality monitoring, or data flywheel design for perception. - Experience with closed-loop simulation for perception model evaluation (neural sim, log sim, scenario-based testing). - Experience at an AV company that has shipped perception to production. 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. Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position. Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles. Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60-1.4(a), 41 CFR 60-300.5(a) and 41 CFR 60-741.5(a) and that these laws are incorporated herein by reference. These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. These regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws. FOR US-BASED ROLES: Applied Intuition is committed to providing an accessible and inclusive application and interview experience to applicants who are disabled veterans and other applicants with disabilities or medical conditions. Reasonable accommodations are available, requesting an accommodation will not affect your candidacy in any way, and you are not required to disclose the nature of your disability or medical condition in order to make a request. If you require an accommodation please contact careers@applied.co. We will work with you!

Requirements

Must-haves

Drive a camera-first perception strategy. The goal is to progressively reduce dependencies on HD maps and lidar. How to get there is part of the job.
Lead training and iteration cycles hands-on. You will be in the data, the eval dashboards, and the failure analysis. When perception regresses in a new geography or road type, you own understanding why and fixing it.
Own model performance across the full deployment surface: highway, urban, residential, ramps, complex intersections, poor weather, hilly terrain. You care about on-vehicle driving outcomes, not just offline metrics.
Work directly with OEM customer programs to understand sensor configurations, target ODDs, and performance requirements. Translate these into model architecture and data strategy.
Recruit, develop, and technically lead a team of perception engineers. Set high technical standards and create a culture of rigorous experimentation and measurement.
Bachelors degree in any field, or equivalent combination of education and work experience.
5+ years in ML/deep learning for perception or 3D scene understanding. Deep hands-on experience training and deploying vision models at scale.
2+ years managing a perception team, with ability to both set direction and contribute to architecture and training decisions directly.
Experience building production perception systems, especially camera-only or camera-first solutions.
Track record deploying perception models to embedded hardware under real-time latency and compute constraints, including device-specific optimizations.
Strong software engineering in Python and C++, comfortable across the stack from training code to onboard inference integration.
Experience scaling perception models across multiple geographies, sensor setups, or vehicle platforms.

Nice-to-haves

Deep familiarity with transformer-based architectures for 3D perception, BEV representations, multi-task learning, and dense prediction.
Familiarity with occupancy-based scene representations, sparse query-based architectures, or temporal aggregation approaches.
Experience reducing or removing map dependencies in perception systems.
Background in autolabel pipelines, data quality monitoring, or data flywheel design for perception.
Experience with closed-loop simulation for perception model evaluation (neural sim, log sim, scenario-based testing).
Experience at an AV company that has shipped perception to production.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlpython

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Paid Time Off

Wellness