Machine Learning Engineer, DoorDash
Delivery Excellence
$140.1-255.8k
+ Equity
Local food delivery platform
Job no longer available
Local food delivery platform
1001+ employees
Job no longer available
$140.1-255.8k
+ Equity
1001+ employees
Company mission
To empower local economies by connecting food lovers with great local restaurants
Role
Who you are
- High-energy and confident — you keep the mission in mind, take ideas and help them grow using data and rigorous testing, show evidence of progress and then double down
- You’re an owner — driven, focused, and quick to take ownership of your work
- Humble — you’re willing to jump in and you’re open to feedback
- Adaptable, resilient, and able to thrive in ambiguity — things change quickly in our fast-paced startup and you’ll need to be able to keep up!
- Growth-minded — you’re eager to expand your skill set and excited to carve out your career path in a hyper-growth setting
- Desire for impact — ready to take on a lot of responsibility and work collaboratively with your team
- 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 Machine Learning, Statistics, Computer Science, Applied Mathematics or other related quantitative fields
- Demonstrated expertise with programming languages, e.g. python, SciKit Learn, Lightgbm, Spark MLLib, PyTorch, TensorFlow, etc
- Deep understanding of complex systems such as Marketplaces, and domain knowledge in two or more of the following: Machine Learning, Causal Inference, Operations Research, Forecasting and Experimentation
- Experience of shipping production-grade ML models and optimization systems, and designing sophisticated experimentation techniques
- You are located or are planning to relocate to San Francisco, CA, Sunnyvale, CA, or Seattle, WA
What the job involves
- As a Machine Learning Engineer, you will have the opportunity to leverage our robust data and machine learning infrastructure to develop inference and ML models that impact millions of users across our three audiences and tackle our most challenging business problems
- You will work with other engineers, analysts, and product managers to develop and iterate on models to help us grow our business and provide the best service quality for our customers
- Build statistical and ML models that run in production to help enhance the consumer experience by reducing cancellations, pickup waiting times, delivery lateness, missing and incorrect items and non fulfilled orders
- Own the modeling life cycle end-to-end including feature creation, model development and prototyping, experimentation, monitoring and explainability, and model maintenance
- Being exposed to new opportunities where delivery quality can be used as a lever for demand shaping, search ranking, customer segmentation, etc
- Mentor and uplevel a talented team of ML Engineers
Our take
DoorDash was an early entrant into the last-mile restaurant delivery business, which is now crowded with the likes of Uber Eats, Postmates and GrubHub. They offer restaurants an end-to-end delivery platform, generating new business and access to a network of delivery drivers.
To differentiate itself in the market, DoorDash focused on areas with fewer competitors and found success in this untapped market. Other factors, such as the company's targeting of restaurants which many not typically offer a delivery service, also contribute to its profitability. The company made its stock market debut in 2020 with one of the biggest IPOs of the year.
However, in light of increasing discontent around DoorDash's commission structure from restaurants, competition remains fierce. The business recently responded by publishing a transparent fee structure, but the number of options open to restaurants means DoorDash must fight to keep its customers loyal. Despite this, by focusing on consumer retention, logistics and technology, the company is likely able to maintain its existing growth and revenue.
Freddie
Company Specialist at Welcome to the Jungle
Insights
13% employee growth in 12 months
Company
Funding (last 2 of 11 rounds)
Jun 2020
$400m
SERIES H
Nov 2019
$100m
SERIES G
Total funding: $2.5bn
Company benefits
- Company stock options
- Work from home stipend
- Unlimited paid time off policy
- Work from home opportunities
- Health insurance
Company HQ
Mid-Market, San Francisco, CA
Leadership
Tony Xu
(CEO)Tony studied at UCB and worked as a Matrix Partners Associate while studying for an MBA at Stanford. He combined this experience to co-found DoorDash in January 2013, and has served as CEO since June 2013.
Stanley Tang
(CPO)Previously studied Computer Science at Stanford, before working at Facebook as a Software Engineer.
Salary benchmarks
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