Research Engineer - AI/RL Infrastructure
$126k - $423k • Sunnyvale • FullTime
Posted 2y ago
Job Location
Sunnyvale
Tech Stack
Remote Work Policy
On-site
Employment Type
FullTime
Categories
AI Research Engineer
About the job
Applied Intuition is seeking a passionate Research Engineer specializing in AI/RL Infrastructure to join our Research Group. This role is perfect for engineers who excel at designing, building, and operating large-scale machine learning systems and enjoy collaborating with researchers to accelerate the development of next-generation physical AI systems. Our Research Group is dedicated to creating cutting-edge technology for challenging applications like end-to-end autonomous driving and robotic generalism, supported by industry-leading tools and infrastructure that provide access to vast datasets and enable deployment of developed methods into various autonomous and robotic systems. Improvements made to our system directly benefit our customers and our business.
Responsibilities
- Design and build training and evaluation infrastructure for AI research, managing large GPU clusters for multimodal sensor data processing.
- Develop robust benchmarking, continuous evaluation, and regression tracking systems to assess model performance on diverse driving data.
- Create large-scale data sampling, dataset generation, and data curation pipelines using advanced AI models for a closed-loop data flywheel.
- Enable high-throughput distributed training across heterogeneous cloud environments, prioritizing reliability, efficiency, and cost-effective scaling.
- Collaborate with AI research, autonomy, and platform teams to transition cutting-edge research into production-ready systems.
Requirements
- Experience building and operating production-grade software systems across the full ML lifecycle (training, evaluation, data, deployment).
- Experience with performance engineering and compute acceleration for large-scale ML training, including profiling, bottleneck analysis, and optimization.
- Strong systems-level debugging skills for diagnosing and resolving issues in 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 a closely related field.
- 1+ year of experience in autonomy and robotics applications or a closely related field.
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