Research Engineer - AI/RL Infrastructure

Responsibilities

• 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 with AI research, autonomy, and platform teams to translate research into production-ready systems

Requirements

• Experience building and operating production-grade software systems across the full ML 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 with PyTorch, CUDA, Ray, Flyte, and K8s

Preferred Qualifications

• Industry experience in relevant topics, specifically self-driving applications
• Senior or Staff level experience

About the Company

Applied Intuition is powering the future of physical AI, creating the digital infrastructure needed to bring intelligence to every moving machine on the planet, including automotive, defense, and robotics.