Applied Machine Learning Engineer
Causal Inference Recommendation
Updated on 2/6/2024
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 • New York, NY, USA • Sunnyvale...
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Kotlin
Python
Tensorflow
Pytorch
Apache Spark
Scala
Natural Language Processing (NLP)
Computer Vision
CategoriesNew
AI & Machine Learning
Requirements
  • 1+ years of industry experience post PhD or 3+ years of industry experience post graduate degree of developing machine learning models with business impact
  • M.S., or PhD. in Statistics, Computer Science, Economics, Math, Operations Research, Physics, or other quantitative fields
  • Strong machine learning background in Python; experience with Spark, PyTorch or TensorFlow preferred
  • Familiarity with Kotlin/Scala
Responsibilities
  • Develop production machine learning solutions, which is a central intelligence to power multiple teams including Sales Operation, Product, and Marketing
  • Partner with engineering and product leaders to help shape the product roadmap leveraging AI/ML
  • Own the modeling life cycle end-to-end including feature creation, model development and deployment, experimentation, monitoring and explainability, and model maintenance
  • Find new ways to use diverse data sources, and modeling techniques, such as NLP, ranking, personalization, image classification, and entity resolution to touch base with merchants at the right time and provide AI driven world class merchant experience
Desired Qualifications
  • Expertise in applied ML for Causal Inference and Recommendation Systems - both classical and deep learning based. Additional familiarity with experimentation, computer vision, and LLMs
  • Ability to communicate technical details to nontechnical stakeholders
  • The desire for impact with a growth-minded and collaborative mindset