AI Performance Engineer
Applied Intuition is a physical-AI company that provides software platforms for developing, validating, deploying, and operating intelligent vehicles and machines.
About Applied Intuition
Founded in 2017, Applied Intuition builds physical-AI tooling and infrastructure, a Vehicle OS, and a Self-Driving System for automotive, defense, trucking, construction, mining, agriculture, and robotics applications.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will profile and optimize distributed training, batch inference, and multi-node scaling. You will develop performance models, reduce GPU idle time, improve cluster goodput, build benchmarking and observability tools, and work with engineers to solve large-scale data and compute problems.
Requirements
- Bachelor’s degree or higher in Computer Science or an adjacent field
- 1+ years of hands-on ML performance engineering experience
- 5+ years of overall experience
- Experience with distributed multi-node training at scale
- Deep familiarity with GPU or accelerator performance concepts
- Experience with high-throughput or batch inference systems
- Fluency in Python and proficiency in C++ or another systems language
- Understanding of machine learning foundations
Responsibilities
- Profile and optimize distributed training end to end
- Optimize large-scale offline and batch inference over sensor logs
- Establish performance models and prioritize optimization opportunities
- Improve multi-node scaling efficiency
- Reduce GPU idle time and improve cluster goodput
- Build benchmarking, observability, and regression-detection tooling
- Collaborate with engineers to solve data and compute problems at scale
Benefits
- Equity