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# AI/RL Infrastructure Engineer: Scale ML Systems

- **Company:** Applied Intuition
- **Location:** Sunnyvale, CA, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Computer Vision, Big Data, Computer Clusters, Nvidia CUDA, Software Debugging, Machine Learning, Open Source Technology, Software Systems, Pytorch, Build Management, Kubernetes, Machine Learning Operations, Data Pipelines
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25196_6303cf6ee66bd780900a7a1f3e931fe1

## About the Role

* 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
 * 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

## Description

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., 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., * 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