ML Optimization Software Engineer
Description For ML Optimization Software Engineer
Applied Intuition, a leading vehicle software supplier trusted by 18 of the top 20 global automakers, is seeking a Senior ML Optimization Software Engineer to join their team. This role presents an exciting opportunity to work at the intersection of machine learning and embedded systems in the automotive industry.
The position requires deep expertise in optimizing ML models and deploying them in production-grade embedded environments. You'll work with cutting-edge technologies across the entire ML framework stack, including PyTorch, JAX, ONNX, TensorRT, CUDA, and XLA. The role combines technical leadership with hands-on development, focusing on optimizing ADAS/AD stacks for various embedded compute platforms.
As a Senior ML Optimization Engineer, you'll be responsible for driving performance optimization, developing compute usage strategies, and working on model pruning and quantization for memory-constrained platforms. You'll collaborate closely with ML engineers and software developers to architect efficient solutions and establish methodologies for performance profiling.
The ideal candidate brings 3+ years of experience with ML accelerators and embedded systems, along with strong software development skills. This is an in-office position at our Mountain View location, offering competitive compensation including a base salary range of $159,053 - $199,295 USD, equity, and comprehensive benefits.
This role offers the opportunity to work on cutting-edge autonomous vehicle technology while solving complex technical challenges in ML optimization. You'll be part of a company that's making a significant impact in the automotive industry, with offices across the globe and a strong focus on innovation and technical excellence.
The position comes with excellent benefits including equity, comprehensive health insurance, 401k with employer match, and various stipends for learning and wellness. If you're passionate about optimizing ML systems and want to contribute to the future of autonomous vehicles, this role offers the perfect blend of technical challenge and industry impact.
Responsibilities For ML Optimization Software Engineer
- Drive ML performance optimization on multiple technologies for ADAS/AD stacks
- Provide technical leadership to the ML model performance optimization team
- Develop compute usage strategies to optimize efficiency and latency
- Work on model pruning and quantization for memory constrained platforms
- Collaborate with ML engineers on efficient model architecture solutions
- Set up methodologies to profile model performance on embedded compute platforms
Requirements For ML Optimization Software Engineer
- Bachelors in Electrical Engineering, Computer Science, Mathematics, Physics or related field
- 3+ years of experience with ML accelerators, GPU, CPU, SoC architecture
- Strong software development skills focused on embedded programming
- Experience profiling and optimizing model performance on embedded compute platforms
- Experience in working with deep learning frameworks (PyTorch, JAX, ONNX)
Benefits For ML Optimization Software Engineer
- Equity (stock options/RSUs)
- Health insurance
- Dental insurance
- Vision insurance
- Life insurance
- Disability insurance
- 401k with employer match
- Learning and wellness stipends
- Paid time off
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