Applied Scientist (Perception Modeling, Autonomous Driving)

TL;DR

Applied Scientist / MLE (Perception Modeling): Apply machine learning techniques to build multi-modal sensor fusion architectures and spatial-temporal representation learners for object detection, tracking, occupancy, and semantic segmentation with an accent on scalable large model training and optimization. Focus on developing distributed fine-tuning methods, pre-training recipes, and evaluation metrics for production systems.

Location: Onsite in Mountain View or San Francisco, California

Salary: $170,000—$216,000 USD

Company

Autonomous driving technology company with the hirify.global Driver powering fully autonomous ride-hail services across multiple U.S. states.

What you will do

• Apply ML techniques to build multi-modal sensor fusion and spatial-temporal learners for object detection, tracking, occupancy, semantic segmentation, and road understanding.
• Develop scalable recipes for large data and model training on Alphabet’s compute infrastructure, including pre-training and post-training methods.
• Create distributed fine-tuning methods enabling multiple developers to improve models without regressions against production systems.
• Develop and maintain model evaluation recipes and metrics for pre-trained and fine-tuned models.

Requirements

• Bachelor’s in Computer Science or equivalent deep learning experience.
• 3+ years experience in Machine Learning and/or Computer Vision.
• Experience with Python.
• Experience with ML frameworks like PyTorch or JAX.

Nice to have

• MS or PhD in Machine Learning, Robotics, or Computer Science.
• Publications at top-tier conferences (CVPR, ICCV, NeurIPS, etc.).
• Experience with C++.

Culture & Benefits

• Hybrid role reporting to a Technical Lead Manager.
• Access to millions of miles of driving data from diverse sensors.
• Discretionary annual bonus, equity incentive plan, and generous benefits.
• Collaboration with research teams at Alphabet.