Applied Intuition

Research Engineer - AI/RL Infrastructure

Applied Intuition$126K — $423K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years in production-grade software systems for ML lifecycle
  • Experience with ML training, evaluation, and deployment
  • Skilled in performance engineering and compute optimization
  • Strong debugging skills in distributed systems
  • Familiar with open-source ML tools and systems
  • Proficient in Pytorch, CUDA, Ray, Flyte, K8s

Responsibilities

  • Design and build AI model training and evaluation infrastructure
  • Establish benchmarking and regression tracking systems
  • Develop data sampling and curation pipelines
  • Enable distributed training in cloud environments
  • Collaborate with research and platform teams for deployment

Benefits

  • Comprehensive health, dental, and vision insurance
  • 401k retirement plan with employer match
  • Learning and wellness stipends
  • Paid time off
  • Potential equity options and/or restricted stock units
Full Job Description
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 AI, with emphasis on the two most challenging applications reshaping our everyday life: end-to-end autonomous driving and robotic generalist. We have a group composed of leading experts from top institutions and companies, recognized for their exceptional academic and industry contributions-including eight Best Paper awards at premier conferences and journals such as CVPR and ICRA. Learn more at appliedintuition.com/research.

Supported by industry-leading tools and infra, researchers can access millions of miles of data from large fleets, and deploy methods they develop into various autonomous 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, you will:
  • Design and build training and evaluation infrastructure to support our current AI research directions, orchestrating massive GPU clusters to process PBs of multimodal sensor data
  • Build robust benchmarking, continuous evaluation, and regression tracking systems to measure model performance across diverse, long-tail real-world driving distributions
  • Develop large-scale data sampling, dataset generation, and advanced data curation pipelines, leveraging state-of-the-art AI models to power a closed-loop data flywheel
  • Enable high-throughput distributed training across heterogeneous cloud environments, 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 skills to diagnose and resolve issues in large-scale distributed training, spanning model code, data pipelines, runtimes, and cluster infrastructure
  • Deep familiarity with the open-source ML and systems ecosystem, with judgment on when to adopt open source versus build in-house
  • Technical experience in: Pytorch, CUDA, Ray, Flyte, K8s
Nice to have:
  • Industry experience on relevant topics (self-driving application preferred)

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.

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the location listed is: $126,000 - $423,000 USD annually.

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.

About Applied Intuition

Applied Intuition is a software company that provides a simulation platform for autonomous vehicles. The platform allows developers to test and validate their autonomous vehicle software in a virtual environment before deploying it on real vehicles. Applied Intuition was founded in 2017 and is headquartered in Mountain View, California.
Learn more about Applied Intuition
Size
200 employees
Industry
Founded
2017

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