Senior ML Engineer - Logistics AI & Optimization

DoorDash, Inc.; San Francisco, Sunnyvale, Seattle (CA, CA, WA); On-site; USD 180,000 - 280,000; Full time

Benefits offered by this job

401(k) plan with employer matching

16 weeks of paid parental leave

wellness benefits

commuter benefits match

medical, dental, and vision benefits

11 paid holidays

disability and basic life insurance

family‑forming assistance

mental health program

Job summary

DoorDash, Inc. is seeking a Machine Learning Engineer for the Drive team, focusing on end-to-end ML systems—feature engineering, model development, experiments, deployment, and monitoring.

You will work on delivery ETA, pickup ETA, merchant prep-time estimation, and order release predictions to improve reliability for merchants and consumers. You will build deep learning models using spatiotemporal signals, apply reinforcement learning to logistics decisions, and create AI-native experiences

Qualifications

• 5+ years of industry experience building and shipping production ML systems with measurable impact.
• Strong experience developing production ML models using PyTorch and distributed data processing tools.
• Experience deploying, monitoring, and maintaining production ML systems end-to-end.

Responsibilities

• Build next-gen ML models for delivery ETA, pickup ETA, and optimization.
• Develop deep learning models using large-scale signals to improve prediction accuracy.
• Apply RL and optimization to improve logistics decisions and marketplace efficiency.
• Build AI-native experiences using LLMs and VLMs for quality signals and verification.
• Design and run online experiments and production monitoring to iteratively improve performance.
• Collaborate with engineers, PMs, data scientists, and platform teams to deploy ML capabilities at scale.

Skills

Production ML systems

Python

PyTorch

Reinforcement Learning

Optimization/OR

LLMs / VLMs

Experimentation

Deployment/Monitoring

Education

Bachelor's/Master's/PhD in a relevant field

Tools

Spark

Airflow

Job description

DoorDash, Inc. is seeking a Machine Learning Engineer for the Drive team, focusing on end-to-end ML systems—feature engineering, model development, experiments, deployment, and monitoring.

You will work on delivery ETA, pickup ETA, merchant prep-time estimation, and order release predictions to improve reliability for merchants and consumers. You will build deep learning models using spatiotemporal signals, apply reinforcement learning to logistics decisions, and create AI-native experiences