About the Team

Come help us build the world's most reliable on-demand, logistics engine for delivery! We are bringing on a talented Machine Learning Engineer to help us develop and improve the ETA and Routing models that power DoorDash's three-sided marketplace of consumers, merchants, and dashers. As a fundamental area of investment for DoorDash, ETA/Routing has among the coolest problems to solve at scale and creates a major impact on the company and its businesses.

About the Role

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.

You’re excited about this opportunity because you will…

  • 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.
  • You can find out more on our ML blog post here.

We’re excited about you because…

  • 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

Experience

  • 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

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey

Compensation

The successful candidate's starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions.  Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.

In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.

DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package for all regular employees that includes a 401(k) plan with an employer match, paid time off, paid parental leave, wellness benefits, and several paid holidays.

Additionally, for full-time employees, DoorDash offers medical, dental, and vision benefits, disability and basic life insurance, family-forming assistance, a commuter benefit match, and a mental health program, among others. 

To learn more about our benefits, visit our careers page here.

The base pay for this position ranges from our lowest geographical market up to our highest geographical market within California, Colorado, District of Columbia, Hawaii, New Jersey, New York and Washington. 

I4
$119,100$175,100 USD
I5
$145,000$213,200 USD
I6
$171,600$252,400 USD

About DoorDash

At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users—from Dashers to merchant partners to consumers. We are a technology and logistics company that started with door-to-door delivery, and we are looking for team members who can help us go from a company that is known for delivering food to a company that people turn to for any and all goods.

DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers. We're committed to supporting employees’ happiness, healthiness, and overall well-being by providing comprehensive benefits and perks including premium healthcare, wellness expense reimbursement, paid parental leave and more.

Our Commitment to Diversity and Inclusion

We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.

Statement of Non-Discrimination: In keeping with our beliefs and goals, no employee or applicant will face discrimination or harassment based on: race, color, ancestry, national origin, religion, age, gender, marital/domestic partner status, sexual orientation, gender identity or expression, disability status, or veteran status. Above and beyond discrimination and harassment based on “protected categories,” we also strive to prevent other subtler forms of inappropriate behavior (i.e., stereotyping) from ever gaining a foothold in our office. Whether blatant or hidden, barriers to success have no place at DoorDash. We value a diverse workforce – people who identify as women, non-binary or gender non-conforming, LGBTQIA+, American Indian or Native Alaskan, Black or African American, Hispanic or Latinx, Native Hawaiian or Other Pacific Islander, differently-abled, caretakers and parents, and veterans are strongly encouraged to apply. Thank you to the Level Playing Field Institute for this statement of non-discrimination.

Pursuant to the San Francisco Fair Chance Ordinance, Los Angeles Fair Chance Initiative for Hiring Ordinance, and any other state or local hiring regulations, we will consider for employment any qualified applicant, including those with arrest and conviction records, in a manner consistent with the applicable regulation.

If you need any accommodations, please inform your recruiting contact upon initial connection.

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