Machine Learning Engineer

1 month ago

Sunnyvale, California, United States DoorDash Full time

About the Role

We're seeking a talented Machine Learning Engineer to join our team and leverage our robust data and machine learning infrastructure to develop inference and ML models that impact millions of users across our three audiences. 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 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.
  • Be 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.
  • Stay up-to-date with the latest advancements in machine learning and data science.

We're excited about you because...

  • You're a high-energy and confident individual who keeps the mission in mind, takes ideas and helps them grow using data and rigorous testing, shows evidence of progress, and then doubles down.
  • You're an owner who is driven, focused, and quick to take ownership of your work.
  • You're humble and willing to jump in and open to feedback.
  • You're adaptable, resilient, and able to thrive in ambiguity, with a fast-paced startup environment.
  • You're growth-minded and eager to expand your skill set and carve out your career path in a hyper-growth setting.
  • You desire impact and are 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 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, or Seattle, WA.

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