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    Applied Machine Learning Engineer - Seattle, United States - DoorDash

    DoorDash
    DoorDash Seattle, United States

    Found in: Talent US C2 - 1 day ago

    DoorDash background
    Description

    About the Role

    We're looking for a passionate Applied Machine Learning expert to join our team. In this role, you will utilize our robust data and machine learning infrastructure to build recommendation system, and implementing new AI solutions to expand restaurants selection and drive their growth. You'll be conceptualizing, designing, and evaluating A/ML solution. You will be expected to demonstrate a strong command of production-level machine learning, a passion to collaborate with multi-disciplinary teams to set the strategy and execute to grow our business.

    You're excited about this opportunity because you will...

  • Develop production machine learning solutions, which is a central intelligence to power multiple teams including Sales Operation, Product, and Marketing
  • Partner with engineering and product leaders to help shape the product roadmap leveraging AI/ML.
  • Own the modeling life cycle end-to-end including feature creation, model development and deployement, experimentation, monitoring and explainability, and model maintenance.
  • Find new ways to use diverse data sources, and modeling techniques, such as NLP, ranking, personalization, image classification, and entity resolution to touch base with merchants at the right time and provide AI driven world class merchant experience.

    • You can find out more on our ML blog

    We're excited about you because you have...

  • 1+ years of industry experience post PhD or 3+ years of industry experience post graduate degree of developing machine learning models with business impact
  • Expertise in applied ML for Causal Inference and Recommendation Systems - both classical and deep learning based. Additional familiarity with experimentation, computer vision, and LLMs
  • M.S., or PhD. in Statistics, Computer Science, Economics, Math, Operations Research, Physics, or other quantitative fields.
  • Ability to communicate technical details to nontechnical stakeholders
  • Strong machine learning background in Python; experience with Spark, PyTorch or TensorFlow preferred.
  • Familiarity with Kotlin/Scala.
  • 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
  • The desire for impact with a growth-minded and collaborative mindset
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