Research Engineer - AI/RL Infrastructure
Applied Intuition2 years ago
Base Salary
$126k - $423k/yr
Responsibilities
- Design and build training and evaluation infrastructure orchestrating massive GPU clusters over petabytes of multimodal sensor data.
- Build benchmarking, continuous evaluation, and regression-tracking systems for diverse real-world driving distributions.
- Develop large-scale data sampling, dataset generation, and data-curation pipelines using advanced AI models.
- Enable high-throughput distributed training across heterogeneous cloud environments with a focus on reliability, efficiency, and cost-aware scaling.
- 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 machine-learning lifecycle, including training, evaluation, data, and deployment.
- Experience with performance engineering and compute acceleration for large-scale machine-learning training, including profiling, bottleneck analysis, and optimization.
- Strong systems-level debugging skills across model code, data pipelines, runtimes, and cluster infrastructure.
- Deep familiarity with the open-source machine-learning and systems ecosystem, including judgment about adopting open source versus building in-house.
- Technical experience with PyTorch, CUDA, Ray, Flyte, and Kubernetes.
- Industry experience with relevant topics, preferably self-driving applications, is a plus.
- Senior/Staff-level experience and potential Tech Lead or Manager capacity are strongly preferred, though candidates at all experience levels may apply.
Benefits
- In-office work primarily 5 days per week, with occasional remote-work flexibility.
- Equity, comprehensive health, dental, vision, life, and disability insurance.
- 401(k) retirement benefits with employer match.
- Learning and wellness stipends and paid time off.
Tech Stack
Categories
About Applied Intuition
Applied Intuition builds software tools, infrastructure, and operating systems for developing, testing, and deploying autonomous and driver-assistance systems across automotive, trucking, defense, construction, mining, and agriculture. It sells enterprise software and services including simulation, sensor data management, HD mapping, and a vehicle OS to OEMs and government customers. Founded in 2017 and headquartered in Sunnyvale, California, it counts 18 of the top 20 global automakers and the U.S. military among its users.