Research Engineer - AI/RL Infrastructure
AI summary of the role
Design and build large-scale ML training and evaluation infrastructure for the Research Group at Applied Intuition, supporting end-to-end autonomous driving and robotic generalist research.
What you’ll do
- Design and build training and evaluation infrastructure to support AI research, orchestrating massive GPU clusters to process PBs of multimodal sensor data
- Build robust benchmarking, continuous evaluation, and regression tracking systems for model performance across diverse real-world driving distributions
- Develop large-scale data sampling, dataset generation, and advanced data curation pipelines using state-of-the-art AI models
- Enable high-throughput distributed training across heterogeneous cloud environments with focus on reliability, efficiency, and cost-aware scaling
What you’ll bring
- Experience building and operating production-grade software systems across the full ML lifecycle (training, evaluation, data, deployment)
- Experience with performance engineering and compute acceleration for large-scale ML training (profiling, bottleneck analysis, optimization)
- Strong systems-level debugging skills for large-scale distributed training issues
- Deep familiarity with open-source ML and systems ecosystem
Technologies
PyTorch · CUDA · Ray · Flyte · Kubernetes · GPU clusters · distributed training · ML infrastructure
About Applied Intuition
Builds the toolchain, vehicle OS and autonomy stacks that automakers, defense and off-road OEMs use to ship AI-driven vehicles.
Series F
Source and classification
Internal deployment & tooling · Evidence for this classification:
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 and team We are looking for a passionate Research Engineer (AI/RL Infrastructure) to join the Research Group at Applied Intuition. This role is ideal for engineers who design, build, and operate state-of-the-art, large-scale ML systems and enjoy working closely with researchers to develop and accelerate the core platform powering next-generation physical AI systems. The mission of the Research Group is to create cutting-edge technology enabling next-generation physical
More from the 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 and team We are looking for a passionate Research Engineer (AI/RL Infrastruct [... source excerpt omitted ...] s and robotic systems including self-driving cars/trucks, autonomous mining/construction machines, humanoid robots and dexterous hands. In addition to your research contributions, you will contribute to and learn from best practices in the autonomy and robotics industries within our fast-paced and customer-focused culture. Improvements deployed to our system immediately help our customers with their programs and deliver value to our business. We are open to all years of experience as long as the necessary requirements are met, including those with potential Tech Lead and Manager capacity; Senior/Staff level experience is strongly preferred for this role. At Applied Intuition, y [... source excerpt omitted ...] vironments, focusing on reliability, efficiency, and cost-aware scaling Collaborate closely with AI research, autonomy, and platform teams to translate cutting-edge research into production-ready systems We’re looking for someone who has: Experience building and operating production-grade software systems across the full machine learning lifecycle, including training, evaluation, data, and deployment Opinions about building a company-wide platform for ML training, evaluation, and deployment Experience with performance engineering and compute acceleration for large-scale ML training, including profiling, bottleneck analysis, and optimization Strong systems-level debugging skil
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