Chewy - Plantation, FL

posted 26 days ago

Full-time - Mid Level
Plantation, FL
Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

Chewy is seeking a Machine Learning Engineer III to join the Merchandising Data Science Team. This role involves leveraging machine learning, data analysis, statistical testing, and software development to create and deploy machine learning models that address critical challenges for Retail Operations. The ideal candidate will have expertise in machine learning and cloud technologies, focusing on deploying and scaling models in cloud environments, and will be responsible for developing backend ML frameworks and engineering pipelines.

Responsibilities

  • Design, develop, and implement machine learning models for various applications, including predictive analytics, natural language processing, and computer vision.
  • Research and implement innovative machine learning algorithms to address specific business challenges.
  • Design and implement cloud architectures for end-to-end machine learning workflows, ensuring scalability, reliability, and performance.
  • Use Infrastructure as Code (IaC) tools to automate the provisioning and management of cloud resources for machine learning.
  • Implement and handle containerization solutions and orchestration tools for deploying and scaling machine learning applications.
  • Collaborate with multi-functional teams to understand requirements and deliver effective solutions.
  • Document code, algorithms and ensure reproducibility.
  • Provide technical mentorship in standard methodologies for model development and deployment to the data science team.
  • Effectively communicate technical concepts and insights to both technical and non-technical customers.

Requirements

  • Graduate Degree (MS or PhD or equivalent experience) in Data Science, Machine Learning, Statistics, Mathematics, or related field.
  • 7+ years of experience in developing and deploying machine learning models and algorithms in a production environment.
  • Strong understanding of statistical analysis, machine learning, and deep learning techniques.
  • Expertise in programming languages such as Python.
  • Proficiency with SQL.
  • Strong understanding of cloud platforms such as AWS.
  • Proficiency in Infrastructure as Code tools (e.g., Terraform, CloudFormation).
  • Experience with containerization and orchestration tools (e.g., Docker, Kubernetes).
  • Proficiency with version control systems (e.g., Git) and coding practices.
  • Strong problem-solving skills and the ability to work independently and in a fast-paced environment.
  • Excellent oral and written communication skills.
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