ML Runtime Optimization Engineer

Applied Intuition, a leading vehicle intelligence company trusted by 18 of the top 20 global automakers, is seeking an ML Runtime Optimization Engineer to join their team in Mountain View, CA. This role combines deep technical expertise in machine learning optimization with practical implementation in automotive and autonomous systems.

The position offers an exciting opportunity to work at the intersection of ML and embedded systems, optimizing critical ADAS/AD stacks for production deployment. You'll be working with cutting-edge ML frameworks (PyTorch, JAX, ONNX, TensorRT) and tackling challenging problems in model optimization, quantization, and deployment on resource-constrained platforms.

The ideal candidate brings 3+ years of experience with ML accelerators and embedded systems, along with strong software development skills. You'll be part of a team that's directly impacting the future of autonomous vehicles and AI-driven machines across multiple industries including automotive, trucking, construction, and defense.

The role offers competitive compensation ($159,053 - $199,295 USD annually) plus equity and comprehensive benefits. While primarily based in-office, the company offers some flexibility for occasional remote work and schedule management. This is an excellent opportunity for someone passionate about optimizing ML systems for real-world applications and wanting to make a significant impact in the autonomous vehicle industry.

The position requires collaboration with ML engineers and software developers, making it ideal for someone who combines technical expertise with strong teamwork skills. You'll be working in a fast-paced environment where your work directly influences the performance and efficiency of autonomous systems used by major global automotive manufacturers.