Senior Machine Learning Engineer - Production ML & RL

DoorDash; Seattle (WA); On-site; USD 204,000 - 299,000; Full time

Benefits offered by this job

401(k) with match

Paid parental leave

Wellness benefits

Commuter benefits matching

Paid time off

Job summary

DoorDash is seeking a Machine Learning Engineer to join the Drive team in Seattle to own ML systems end-to-end—from feature engineering to deployment and monitoring.

You will build models for delivery ETA, leverage large-scale signals, and collaborate across engineering, product, and data science to bring capabilities into production. Equity opportunities and comprehensive benefits are included.

Qualifications

• 5+ years of industry experience building and shipping production ML systems with measurable business impact.
• Experience with PyTorch and distributed data processing technologies such as Spark and Airflow.
• Experience deploying, monitoring, and maintaining production ML systems end-to-end.

Responsibilities

• Build next-generation ML models for delivery ETA, pickup ETA, and order release prediction.
• Develop deep learning models using large-scale signals to improve prediction accuracy.
• Apply reinforcement learning and optimization to improve logistics decisions.
• Build AI-native experiences using LLMs and VLMs for structured quality signals.
• Design and run online experiments and production monitoring to improve performance.
• Collaborate with engineers, PMs, data scientists, and platform teams to productionize ML capabilities.

Skills

Python

PyTorch

Deep Learning

Reinforcement Learning

LLMs/VLMs

Spark

Airflow

Claude Code

Codex

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Education

Bachelor's/Master's/PhD in CS/related field

Tools

PyTorch

Spark

Airflow

Claude Code

Codex

Cursor

Job description

DoorDash is seeking a Machine Learning Engineer to join the Drive team in Seattle to own ML systems end-to-end—from feature engineering to deployment and monitoring.

You will build models for delivery ETA, leverage large-scale signals, and collaborate across engineering, product, and data science to bring capabilities into production. Equity opportunities and comprehensive benefits are included.