Applied Intuition
Research Engineer - AI/RL Infrastructure
$126K–$423K
Sunnyvale · On-site · Full-time · Posted Sep 17, 2024
- Experience
- Open to all years of experience; requires 1+ year in autonomy, robotics, or a closely related field. Senior/Staff-level experience strongly preferred.
- Education
- Master’s or PhD in machine learning and computer vision with autonomy and robotics applications, or a closely related field.
About the job
Build and operate large-scale ML and reinforcement-learning infrastructure supporting research in autonomous driving and robotics.
What you'll do
- Build training, evaluation, benchmarking, and regression-tracking infrastructure using large GPU clusters and multimodal sensor data.
- Develop distributed training, data sampling, dataset generation, and data-curation pipelines.
- Collaborate with research, autonomy, and platform teams to turn research into production-ready systems.
What they ask for
- Production-grade software systems experience across the machine-learning lifecycle, including training, evaluation, data, and deployment.
- Experience with performance engineering and compute acceleration for large-scale ML training, plus distributed-systems debugging.
- Technical experience with Pytorch, CUDA, Ray, Flyte, and K8s.
- Master’s or PhD in machine learning, computer vision, autonomy, robotics, or a closely related field; at least 1 year of relevant experience.
Nice to have
- Relevant industry experience, preferably in self-driving.
- Senior/Staff-level experience is strongly preferred.
Pay
$126K – $423K USD base salary
Tools
Pytorch, CUDA, Ray, Flyte, K8s
AI focus
Infrastructure for AI research in autonomous driving and robotics, including large-scale model training, evaluation, data curation, and closed-loop data pipelines.
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