Data Engineer - Axion

Applied Intuition•Sunnyvale, CA

9d•$200,000 - $275,000•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

5+ years of relevant work experience
Familiarity with modern ML infrastructure, data-centric AI approaches and running large-scale jobs on GPUs
Created or worked on microservices and/or databases for data-oriented software
A hunger to learn and grow into a position of ownership and impact on a new product team
U.S. citizenship (legally required) and eligibility to obtain a security clearance

Nice To Haves

Full-stack experience React, TypeScript Python, Golang or similar
Experience with Docker, Kubernetes, Opensearch and Postgres
Direct experience with foundation models, including LLMs and VLMs, for data automation tasks
Background in autonomous driving or robotics perception
Experience with active learning, auto-labeling, or human-in-the-loop ML systems

Responsibilities

Construct optimized data pipelines to run ML models
Evolve our data engine architecture to scale high-fidelity labels, reduce annotation costs, and accelerate ML iteration cycles
Integrate foundation models (LLMs, VLMs, and multimodal models) to automate and enhance labeling, quality assurance, and data discovery
Leverage software-in-the-loop and hardware-in-the-loop testing
Interact with the DoD customer to understand their use cases, requirements, and triage needs during field events to deliver a superior customer experience