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Machine Learning Engineer III

2 months ago

Minneapolis, Minnesota, United States Chewy Full time

Our Mission:

At Chewy, we're on a mission to redefine the future of fulfillment by building a high-fidelity Digital Twin - a real-time, AI-driven simulation that mirrors our fulfillment centers down to the last detail. Using the groundbreaking Nvidia Omniverse platform, we're creating a new era of innovation and efficiency.

About the Role:

We're seeking a highly skilled Machine Learning Engineer III to join our team in Boston, MA, or Minneapolis, MN. As a key member of our team, you'll be responsible for designing, testing, and scaling effective machine learning frameworks, systems, and models to improve the usefulness of data and predictive applications.

Key Responsibilities:

  • Apply artificial intelligence and/or machine learning methods to design, test, and scale effective, reliable frameworks, systems, and models to improve the usefulness of data and predictive applications.
  • Research, implement, and test machine learning algorithms and tools to tackle data challenges and to improve quality and reliability of data.
  • Develop machine learning applications according to requirements; design, code, test, deploy, and iterate on machine learning systems.
  • Work with Data/Research Scientists, Robotics/Software Engineers, and Product Managers to develop and support software for new machine learning products.
  • Formalize assumptions about model behavior, define outliers, develop methods to systematically identify and address them, and explain or resolve these issues.
  • Communicate research findings and technical insights to business customers of varying technical backgrounds, providing clear recommendations and educating customers.

Requirements:

  • 5+ years of hands-on experience in developing and deploying optimization, predictive, and machine learning models.
  • An advanced degree (undergraduate, M.S. or equivalent experience) in Operations Research, Statistics, Applied Mathematics, Physics, Data Science, or equivalent quantitative fields such as Engineering, Computer Science with a background in machine learning.
  • Experience in MLOps best practices and proven use of Software Engineering best practices.
  • Excellent verbal and written communication skills and the ability to explain details of complex concepts to non-expert partners in a simple and understandable way.
  • Experience coding and analyzing data using Python, SQL, or R.
  • Experience with frameworks such as PyTorch, TensorFlow, or Keras.

Bonus Requirements:

  • Experience with Amazon Web Services tools such as SageMaker or other similar platforms.
  • Experience of translating ambiguous customer requirements into clear problem definitions and delivering them.
  • Experience with Robotics or Computer Vision systems.