Ingeniero de aprendizaje automático - Excelencia en la entrega

Acerca del equipo

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. As a fundamental area of investment for DoorDash, Delivery Excellence has among the coolest problems to solve at scale and creates a major impact on the company and our customers. We are looking for Machine Learning Engineers, Economists, Mathematicians, Statisticians, and Senior Quantitative Researchers from all disciplines.

Acerca del puesto

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.

Le entusiasma esta oportunidad porque...

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

Estamos entusiasmados contigo porque...

• 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

• Más de 1 año de experiencia en la industria después del doctorado o más de 3 años de experiencia en la industria después del posgrado en desarrollo de modelos de aprendizaje automático con impacto empresarial.
• 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

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.

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