Senior Software Engineer, Perception, Multi-Platform

The Perception Team at Waymo builds the system that "sees" the world around the self-driving car. We conduct novel research to address real-world perception problems and collaborate with research teams at Alphabet. Here at Waymo, we have access to millions of miles of driving data from a diverse set of sensors, enabling researchers like you to develop complex models and techniques at scale. Improvements deployed to our system can immediately advance our large fleet of autonomous vehicles.

The HAL (Hardware Abstraction Layer) team's job is to make sure that sensors "just work" for the entire autonomous driving vehicle software stack. We design APIs that abstract away hardware details and provide convenient and fast access to the GBs of information from the physical sensors. We are responsible for the initial processing of the raw sensor signals and use the sensor data to derive compact, higher level information about the environment around the self-driving car that feeds into the Perception and Planning models which dictate the car's responses.

In this hybrid role, you will report to a Technical Lead Manager:

You will:

• Work with a creative team of people who are responsible for the bring-up of new hardware platforms (vehicles, sensors, compute) and for building a multi-platform software stack.
• Develop a Hardware Abstraction Layer (HAL) that provides sensor data to Perception through a unified API.
• Work on a bleeding edge project at the intersection of traditional robotics and modern ML techniques.

You have:

• BS in Computer Science, Robotics, similar technical field of study, or equivalent practical experience
• 5+ years of industry experience
• Experience with sensor data processing (Lidar, camera, or Radar)
• Experience with building, integrating, debugging and evaluating ML-based systems
• Experience programming in C++ with robust and efficient code
• Software architecture skills

We prefer:

• MS or PhD in Computer Science, Robotics, similar technical field of study, or equivalent practical experience
• Experience with autonomous vehicles (L4) or ADAS systems (L2/L3)
• Experience with bring-up of new sensors or vehicle platforms
• Experience applying Machine Learning to Perception problems

#LI-Hybrid