Applied Scientist / MLE, Perception Modeling

Tech Stack

Responsibilities

• Apply machine learning techniques to build multi-modal sensor fusion architectures and spatial-temporal representation learners for object detection and tracking, occupancy and semantic segmentation, road understanding.
• Develop scalable recipes for large data, large model training running on Alphabet’s compute infrastructure, create methods and recipes for pre-training and post-training.
• Develop methods and recipes for distributed fine-tuning enabling multiple developers to simultaneously improve the model, develop methods and recipes to avoid regression against a production system.
• Develop and maintain model evaluation recipes and metrics for measuring and improving performance of pre-trained and fine-tuned models.

Benefits

• Equity
• Health Insurance
• Learning Budget
• Remote Work

Culture

Requirements