MS/PhD Perception Robotics Intern - Sensor Calibration & ML

Waymo LLC; Mountain View (CA); Hybrid; USD 96,000 - 117,000; Full time

Benefits offered by this job

Hourly pay for Masters and PhD levels

Hybrid onsite internship

Generous benefits programs (subject to

eligibility requirements

Job summary

Waymo LLC is offering a hybrid onsite internship within the Perception team, focusing on sensor calibration for autonomous driving. You will join efforts to align sensor data and deploy calibration systems across platforms, collaborating with hardware, software, and operations teams.

The role targets MS/PhD students in CS or Robotics and requires C++ experience. Preference for those who have deployed software in complex systems and who can contribute ML-based calibration ideas.

Qualifications

• Enrolled in a MS/PhD program in Computer Science, Robotics, or a similar technical field of study.
• Experience in C++.
• Experience deploying software as part of a complex system.

Responsibilities

• Help Waymo scale the sensor calibration algorithms to seamlessly support many different hardware architectures by developing the next-generation calibration system.
• Develop, evaluate, and deploy new initiatives for the next-generation calibration system.
• Evaluate and deploy ML-based calibration systems in new areas not yet covered in the literature.
• Collaborate with highly experienced colleagues across hardware, software, and operations on deploying real world robotic system.

Skills

C++

Education

MS/PhD program in Computer Science, Robotics, or a similar technical field

Job description

Waymo LLC is offering a hybrid onsite internship within the Perception team, focusing on sensor calibration for autonomous driving. You will join efforts to align sensor data and deploy calibration systems across platforms, collaborating with hardware, software, and operations teams.

The role targets MS/PhD students in CS or Robotics and requires C++ experience. Preference for those who have deployed software in complex systems and who can contribute ML-based calibration ideas.