Machine Learning Engineer, Forecast Platform

About the TeamCome 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 improve the operational efficiency of DoorDash's three-sided marketplace of consumers, merchants, and dashers. The Forecasting Platform provides a unique opportunity to have a broad impact on the business ensuring we can quickly respond to a rapidly changing operational environment. The team supports projects across all of our major pillars (e.g. supply / demand, auto-scaling infrastructure, support optimization) as well as the development of an internal decision platform for time series.About the RoleAs a Machine Learning Engineer, you will have the opportunity to leverage our robust data and machine learning infrastructure to develop 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.You're excited about this opportunity because you will...• Build time-dependent statistical and ML models that solve product needs across our verticals - e.g. matching supply / demand, predicting support needs, providing insights to our internal platforms (ads, experiments, merchant), auto-scale infrastructure and optimize business processes such as promotions• Own the modeling life cycle end-to-end including feature creation, model development and prototyping, experimentation, monitoring and explainability, and model maintenance• Contribute to the development of our in-house Forecasting Self-Service Platform and proprietary Forecasting Repository to uplevel our capabilities• Research new tools within the Forecasting space (e.g. TimeGPT, LLM extensions)• You can find out more on our ML blog post hereWe'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 teamExperience• M.S. and 3+ or PhD. and 1+ year(s) experience of developing advanced statistical and machine learning models in production• Demonstrated expertise with object-oriented programming and ML Libraries, 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• Experience of shipping production-grade ML models and optimization systemsAbout DoorDashAt 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 InclusionWe'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.CompensationThe location-specific base salary range for this position is listed below. Compensation in other geographies may vary.Actual compensation within the pay range will be decided based on factors including, but not limited to, skills, prior relevant experience, and specific work location. For roles that are available to be filled remotely, base salary is localized according to employee work location. Please discuss your intended work location with your recruiter for more information.DoorDash cares about you and your overall well-being, and that's why we offer a comprehensive benefits package, for full-time employees, that includes healthcare benefits, a 401(k) plan including an employer match, short-term and long-term disability coverage, basic life insurance, wellbeing benefits, paid time off, paid parental leave, and several paid holidays, among others.In addition to base salary, the compensation package for this role also includes opportunities for equity grants.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. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on June 20, 2024.Please see the independent bias audit report covering our use of Covey here.California Pay Range:$140,100-$210,100 USDWashington Pay Range:$140,100-$210,100 USD