Senior Machine Learning Engineer, Sensor Validation

Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you’re a software engineer or researcher who’s curious and passionate about Level 4 autonomous driving, we'd like to meet you.
Within Perception, the Sensor Health team's job is to make sure that sensors "just work" for the entire self-driving car software stack. We make sure that all sensors are properly calibrated and consistently monitored at all times. We are often the firsts to algorithmically process data from next-generation sensors on next-generation vehicle platforms and work closely with both hardware and software teams to provide the best possible sensor data from our many sensors perfectly aligned to our upstream customers. To this end, we develop sensor data alignment and calibration algorithms, a growing sensor health backend, and deploy our systems both into the Waymo Driver and our log processing backend.

This role follows a hybrid work schedule and reports to a Technical Lead Manager.
You will:

• Develop and implement state-of-the-art sensor validation algorithms for analyzing the health of our sensor suites
• Implement onboard fault detection, isolation, and recovery solutions using cutting edge ML approaches
• Work on sensor fusion algorithms that scale for heterogeneous sensor and multi-platform systems
• Develop a data flywheel approach to automatically scale sensor validation approaches
• Work with in-house hardware and perception teams on novel sensing modalities and next-generation perception solutions

You have:

• MS in Computer Science, Robotics, Math, Physics or equivalent industry experience
• 3+ years of experience in Machine Learning, with a strong focus on deep learning for perception tasks.
• Deep understanding of multiple sensing modality principles to work with laser, radar, and image products
• Strong C++ skills and ability to write high quality production level code.
• Experience with Python
• Experience with ML frameworks like PyTorch or JAX
• Familiarity with machine learning techniques applied to sensor fusion, sensor calibration, or positioning problems.

We prefer:

• PhD in Computer Science, Robotics, Math, Physics or equivalent industry experience
• Experience developing and using tools for large-scale data analysis and visualization (e.g., SQL, Python with libraries like NumPy, Pandas, Matplotlib).
• Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI
• Experience in the autonomous vehicle (AV) or robotics industry, particularly with real-time on-device perception systems.