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 improve the delivery service quality for DoorDash's three-sided marketplace of consumers, merchants, and dashers. DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last-mile logistics in the long term.. We are looking for Machine Learning Engineers, Economists, Mathematicians, Statisticians, and Senior Quantitative Researchers from all disciplines. 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 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 statistical and ML models that run in production to help enhance the consumer experience by reducing missing and incorrect items, cancellations, estimated arrival times, 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 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 3+ years of industry experience post PhD or 5+ 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 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 to all regular employees, which includes a 401(k) plan with employer matching, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act) (for salaried roles: flexible vacation, plus 80 hours of paid sick time per year; for hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week), 16 weeks of paid parental leave, a wellness benefit, and a commuter benefit match. Additionally, for full-time employees, DoorDash offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others. To learn more about our benefits, visit our careers pagehere . The base pay for this position ranges from our lowest geographical market up to our highest geographical market within the United States.
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