Software Engineer

Applied Intuition•Sunnyvale, CA

4d•$182,600 - $243,900•Onsite

About The Position

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 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.

Requirements

Requires a Bachelor’s or foreign degree equivalent in Computer Science or related field
One (1) year of experience in job offered or any occupation in which the required experience was gained. Employer will accept knowledge gained through employment experience, research, or academic courses of study:
Python
Go or C++
Building scalable software systems and data-intensive pipelines
Building and training models using deep learning frameworks
Data modeling
SQL
Modern Version control (GIT)
Deep Neural Networks, Generative Models, or Reinforcement Learning
Cloud infrastructure
Containerization
Orchestration tools to deploy and scale software services

Responsibilities

Design, implement, and deploy software and machine learning components focused on behavior prediction and environmental interactions.
Build scalable software to support inference and decision-making in dynamic environments.
Build and optimize pipelines to process complex datasets, including time-series and sensor data.
Transform raw logs into structured datasets optimized for training large-scale modeling and forecasting algorithms.
Develop testing and evaluation frameworks to validate system performance within simulated environments.
Measure model accuracy and logic robustness against real-world ground truth data to drive iterative improvements.
Implement and refine algorithms for state estimation and decision planning.
Leverage generative or deep learning methods to improve the efficiency and accuracy of models dealing with uncertainty.
Collaborate with cross-functional teams to integrate models into production-grade systems, ensuring low-latency performance and seamless interaction with upstream modules.
Develop and maintain software tools, libraries, and infrastructure for visualizing model outputs, managing experiment tracking, and automating workflows for continuous model delivery.
Maintain high code quality through modular design, implementing rigorous testing strategies (including mocks and regression tests) suitable for complex, data-intensive systems.