Ml Runtime Optimization Engineer
Applied Intuition- Location
- Not specified
- Work mode
- On-site
- Type
- full time
- Listed
Applications go directly to Applied Intuition. Ramai takes no fee for placement and no money for ranking.
[ About this role ]
ML Runtime Optimization Engineer at Applied Intuition focused on optimizing ML models for embedded runtime environments. The role involves driving performance optimization across various technologies for ADAS/AD stacks, developing compute usage strategies, and working on model pruning and quantization for memory-constrained platforms.
Skills and focus areas
- ml model optimization
- embedded systems
- pytorch
- jax
- onnx
- tensortrt
- cuda
- xla
- triton
- model pruning
- quantization
- latency optimization
Summary written by Ramai from the original posting. Full details and requirements are on Applied Intuition’s careers page.
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