Staff Software Engineer, Simulation ML Infrastructure
Waymo is seeking a Staff Software Engineer to join the Simulation Machine Learning Infrastructure team in London. This team focuses on developing scalable AI/ML infrastructure to enhance the realism and effectiveness of simulations used for testing and training the Waymo Driver, the company's autonomous driving technology.
In this role, you will lead the development of advanced AI/ML infrastructure for large-scale foundation models within ML accelerator-friendly simulations. Your responsibilities will include designing and scaling distributed systems that support extensive dataset generation and model training, collaborating with cross-functional teams to align technical deliverables with business objectives, and mentoring junior engineers to foster a collaborative culture.
The ideal candidate will have a Bachelor's degree in Computer Science, Robotics, or a related technical field, along with at least 5 years of professional software engineering experience, including 3 years focused on machine learning infrastructure. Preferred qualifications include a Master's degree, over 10 years of experience, and expertise in machine learning frameworks such as DeepSpeed, PyTorch, or TensorFlow. Familiarity with distributed training techniques and a deep understanding of state-of-the-art machine learning models are also highly valued.
Waymo offers a competitive base salary ranging from £155,000 to £163,000 GBP for this full-time position. Employees are also eligible to participate in the company's discretionary annual bonus program, equity incentive plan, and comprehensive benefits program, which includes health and wellness support, financial wellness resources, flexible time off, and family support options.
Joining Waymo means becoming part of a pioneering company dedicated to making autonomous driving a reality. The company fosters a culture of innovation and collaboration, providing opportunities for personal and professional growth. Employees have access to state-of-the-art facilities and resources, contributing to the development of cutting-edge technology that aims to improve global mobility and safety.