Machine Learning Engineer, DoorDash
ETA & Routing
$140.1-210.1k
In addition to base salary, the compensation package for this role also includes opportunities for equity grants
Local food delivery platform
Open for applications
Local food delivery platform
1001+ employees
Open for applications
$140.1-210.1k
In addition to base salary, the compensation package for this role also includes opportunities for equity grants
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 advanced machine learning models with business impact
- M.S., or PhD. in Computer Science, Statistics, or other related quantitative fields
- 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
- 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 optimization ETA and Routing models that impact millions of users across our three audiences and tackle our most challenging business problems
- You will work with other data scientists, engineers, and product managers to develop and iterate on models to help us grow our business and provide better service quality for our customers
- 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
Otta's take
Theo Margolius
COO of Otta
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.
Insights
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 values
- We are doers
- We are learners
- We are leaders
- We are one team
Company HQ
Mid-Market, San Francisco, CA
Founders
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.
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