below marketmost similar roles pay hereabove market
This role pays more than
64%
of similar roles. Most pay
$211,200–$254,750
— the blue band above.
At the midpoint, this role pays about
$251k
versus about
$233k
for comparable roles.
Based on 240 similar postings.
Employer
About DoorDash, Inc
DoorDash, Inc. is an American company operating online food ordering and food delivery. It trades under the symbol DASH. With a 56% market share, DoorDash is the largest food delivery platform in the United States.
DoorDash, Inc currently has
97 open roles
on FindRole.
Listed pay typically runs
$163,800–$240,900
across 96 roles with salary data.
The Staff Machine Learning Engineer, Personalization joins the Personalization team to develop modern growth and personalization models for the retail and grocery delivery business. In this role, you will conceptualize, design, implement, and validate algorithmic improvements to create a personalized shopping experience. You will build production machine learning solutions to make consumer search experiences more relevant across various retail categories while mentoring junior team members and leading cross-functional pods. Key technical requirements include proficiency in Python, PyTorch, or TensorFlow, and expertise in applied ML for Causal Inference and Recommendation Systems, including deep learning and MAB algorithms. You will also utilize AI coding tools like Claude Code, Codex, and Cursor to manage the full software development lifecycle while solving complex end-user problems within the logistics engine.
What does a Machine Learning Engineer earn in California?
Median $235750 from 200 postings across 34 companies.
Python
LLMs
Deep Learning
Graph Neural Networks
NLP
Machine Learning
Information Retrieval
Data Mining
Statistics
Gradient-Boosted Trees
Regression
Data Workflows
Production ML Systems
Observability
Responsible AI
Machine Learning
Python
Golang
TensorFlow
PyTorch
Deep Learning
Recommendation Systems
Feature Pipelines
Model Training
Regression Analysis
Hypothesis Testing