Research Engineer - AI/RL Infrastructure

The role

You will design and build training and evaluation infrastructure to support AI research directions. This includes orchestrating GPU clusters, building benchmarking systems, and developing data curation pipelines.

What you will do

• Design and build training and evaluation infrastructure to support AI research directions
• Orchestrate massive GPU clusters to process PBs of multimodal sensor data
• Build robust benchmarking, continuous evaluation, and regression tracking systems
• Develop large-scale data sampling, dataset generation, and advanced data curation pipelines
• Enable high-throughput distributed training across heterogeneous cloud environments
• Collaborate closely with AI research, autonomy, and platform teams

Required qualifications

• Experience building and operating production-grade software systems across the full machine learning lifecycle
• Experience with performance engineering and compute acceleration for large-scale ML training
• Strong systems-level debugging skills for large-scale distributed training
• Deep familiarity with the open-source ML and systems ecosystem
• Technical experience in Pytorch, CUDA, Ray, Flyte, K8s
• Masters or PhD in machine learning and computer vision with autonomy and robotics applications or closely related field
• 1+ year of experience in autonomy and robotics applications or closely related field

Nice to have

• Senior/Staff level experience
• Industry experience on relevant topics (self-driving application preferred)

Benefits

• Base salary
• Equity (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
• Paid time off

About the company

Applied Intuition, Inc. is a Silicon Valley company creating digital infrastructure for physical AI. It services the automotive, defense, trucking, construction, mining and agriculture industries.