Machine Learning Engineer - Autotuning

Zoox, a pioneering company in autonomous vehicle technology, is seeking a Machine Learning Engineer to join their innovative team. This role sits at the intersection of artificial intelligence and autonomous driving, focusing on developing systems that evaluate and enhance autonomous driving behaviors through learning from expert human drivers.

The position offers a competitive compensation package ranging from $160,000 to $245,000 in base salary, complemented by Amazon RSUs and Zoox Stock Appreciation Rights. Located in Foster City, CA, with a hybrid work arrangement, this role provides an opportunity to work on cutting-edge technology that will shape the future of urban mobility.

As a Machine Learning Engineer, you'll be responsible for designing and implementing ML systems that learn from human driving data, developing evaluation methods for autonomous driving, and creating AutoML systems to optimize driving software. You'll work with large-scale datasets and distributed training pipelines while collaborating with cross-functional teams including planners, simulation experts, and infrastructure teams.

The ideal candidate should possess a strong educational background in Machine Learning or Computer Science (BS/MS/PhD) and demonstrate proficiency in Python and PyTorch. Experience with building ML systems, training and deploying models, and working with large datasets is essential. The role offers comprehensive benefits including health insurance, paid time off, equity opportunities, and various insurance coverages.

Zoox is committed to diversity and inclusion, welcoming candidates from various backgrounds and experiences. The company is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. This position offers an exciting opportunity to be part of a fast-moving team working at the forefront of autonomous vehicle technology and the future of urban transportation.