Machine Learning Engineer
ETA & Routing
Updated on 4/13/2024
DoorDash

10,001+ employees

Local food delivery from restaurants
Company Overview
DoorDash is working to empower local communities and in turn, creating new ways for people to earn, work, and thrive. The company operates the largest food delivery platform in the United States.
Consumer Goods

Company Stage

Series H

Total Funding

$2.5B

Founded

2013

Headquarters

San Francisco, California

Growth & Insights
Headcount

6 month growth

0%

1 year growth

-2%

2 year growth

-9%
Locations
Seattle, WA, USA • San Francisco, CA, USA • Sunnyvale, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
Pytorch
Apache Spark
CategoriesNew
AI & Machine Learning
Applied Machine Learning
Deep Learning
Requirements
  • M.S., or PhD. in Computer Science, Statistics, or other related quantitative fields.
  • 1+ years of industry experience post PhD or 3+ years of industry experience post graduate degree of developing advanced machine learning models with business impact.
  • Strong background in Deep Learning and OSS ML technologies such as Spark, PyTorch, Airflow with hands-on experience in production.
  • Demonstrated expertise with programming languages e.g. python and machine learning libraries e.g. LightGBM, Spark MLLib, PyTorch, etc.
  • Deep understanding of complex systems such as Marketplaces, and domain knowledge in two or more of the following: Deep Learning, Reinforcement Learning, Operations Research, and Forecasting.
  • Experience of shipping production-grade ML models and optimization systems, and designing sophisticated experimentation techniques.
Responsibilities
  • Build Deep Learning models for next-generation ETA that provide the most accurate, scalable and robust time predictions and enhance the consumer experience.
  • Build Machine Learning models in the routing space, which can be used as the single source of truth across internal teams to positively impact the top-line business metrics.
  • Own the modeling life cycle end-to-end including feature creation, model development and testing, experimentation, monitoring and explainability, and model maintenance.
  • Being exposed to new opportunities where ETA/Routing can be used as a lever that benefits new business, new markets, and new regions.