Machine Learning Engineer, Drive

What you'll do

• Build machine learning models for delivery ETA, merchant prep-time estimation, and order release prediction.
• Develop deep learning models using spatiotemporal, marketplace, and behavioral signals to improve accuracy.
• Apply reinforcement learning and optimization techniques to improve logistics decision-making and marketplace efficiency.
• Create AI-native products using LLMs and VLMs to transform images into structured quality signals.
• Manage the end-to-end machine learning lifecycle including feature engineering, development, deployment, and monitoring.
• Design and execute rigorous online experiments to iterate on model performance.
• Develop production-scale systems using PyTorch, Spark, and Airflow.

What we're looking for

• Must have a Bachelor's, Master's, or PhD degree.
• Requires 5+ years of industry experience building and shipping production machine learning systems with measurable business impact.
• Must have strong software engineering skills in Python and experience with modern ML infrastructure and tooling.
• Requires experience developing models using PyTorch and distributed data processing technologies like Spark and Airflow.
• Must have experience building, deploying, monitoring, and maintaining production ML systems end-to-end.
• Requires deep expertise in at least one area: Deep Learning, Reinforcement Learning, Optimization/Operations Research, or LLMs/VLMs.
• Experience applying machine learning to estimation, ranking, prediction, optimization, or decision-making problems at production scale is required.
• Must be located in or willing to relocate to San Francisco, Sunnyvale, or Seattle.