Lead the design, development, and deployment of machine learning models to detect road disruptions and maintain road signs from various signals (e.g., traffic data, vehicle telemetry, vehicle sensors, imagery etc.).

Develop and improve ML algorithms for inferring road closures and speed limits, fusing data from multiple sensors and sources like vehicle sensor observations (VSO), location data, Waze, and third-party data.

Build and maintain scalable data pipelines for training, evaluation, and inference using Google's infrastructure.

Collaborate closely with other engineers, product managers, data analysts, and operations teams to define requirements, integrate ML solutions, and drive impact on map data quality.

Provide technical leadership and mentorship to junior engineers on the team.

Bachelor’s degree or equivalent practical experience.

8 years of experience in software development.

5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

Experience with common machine learning techniques and technologies.

Experience building or interacting with Generative AI or Applied AI applications.