Gm Cruise - San Francisco, CA
posted 4 months ago
At Cruise, we are at the forefront of developing self-driving vehicles that aim to transform urban mobility. Our Behaviors Teams are tasked with creating machine learning models that enable our autonomous vehicles (AVs) to navigate complex urban environments safely and efficiently. This role involves tackling a variety of exciting challenges, such as building decision-making models that allow our AVs to make intelligent driving decisions by considering the actions of nearby agents, including other vehicles, pedestrians, and animals. Additionally, the team is responsible for generating safe and feasible trajectories for our vehicles to follow in dynamic urban settings, ensuring that the driving experience is both comfortable and safe for passengers. The Behaviors Teams collaborate closely with our Perception partners to gather data from various sensors, high-fidelity maps, and simulation data, which are crucial for developing the technologies that underpin our self-driving capabilities. Furthermore, we work alongside Robotics and Controls partners to ensure that our vehicles can accurately follow the planned paths. This position is versatile, encompassing a wide range of applied machine learning research and development aimed at overcoming the challenges presented by urban driving. In this role, you will be expected to explore, prototype, validate, and iterate on new algorithms from a research perspective, while also driving efforts to optimize and refine on-road performance for models as they transition to production. As a technical leader within the department, you will guide current and future technology choices, balancing the operational impact of different technology trade-offs based on the company's needs. You will also play a key role in enabling other engineers on the team to be more effective through the design and implementation of extensible and maintainable code. Your ability to influence others and build consensus will be essential, especially during technical discussions that may involve differing opinions.