Sr Software Engineer (Machine Learning)

2 Months ago • 8 Years +

About the job

Job Description

Sr Software Engineer (Machine Learning) with 8+ years of experience, expertise in Python, TensorFlow/PyTorch, Azure, and all phases of the ML lifecycle. Must have experience in exploratory data analysis, deep learning, and deployment understanding for MLOps.
Must have:
  • Python experience
  • TensorFlow/PyTorch
  • Azure experience
  • ML lifecycle
Good to have:
  • MLOps experience
  • Docker/Kubernetes
  • LLMs in RAG
  • E-commerce domain
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About the job

Responsibilities

JOB DESCRIPTION

▪ Demonstrate a deep knowledge of, and ability to operationalize, leading data & analytic technologies and best practice

▪ Partner end-to-end with Product Managers to understand customer requirements and design prototypes and bring ideas to production

▪ Strategize, design, build, harden, and maintain the core infrastructure used to operate our machine learning platform and lifecycle

▪ Be part of the senior team responsible for defining our technology strategy, roadmap and priorities for our organization

▪ Manage the automation of every aspect of our infrastructure to remove as much as possible any human intervention

Desirable Competencies

▪ 8+ year of work experience

▪ We develop real products. You need to be an expert in design, coding, and scripting

▪ Facilitate problem diagnosis and resolution in technical and functional areas.

▪ Encourage change, especially in support of data engineering best practices and developer satisfaction.

▪ Write high-quality code that is consistent with our standards, creating new standards as necessary.

▪ Demonstrate correctness with pragmatic automated tests.

▪ Review the work of other engineers in a collegial fashion to promote and improve quality and engineering practices

▪ Develop strong working relationships with others across levels and functions

▪ Participate in, and potentially coordinate, Communities-of Practice in those technologies in which you have an interest

▪ Participate in continuing education programs to grow your skills both technically and in the Williams-Sonoma business domain.

Required

▪ Experience in python

▪ Experience in Tensorflow or PyTorch.

▪ Experience in Azure.

▪ Working experience of all phases of machine learning lifecycle.

▪ Experience in exploratory data analysis

▪ Good understanding, knowledge and Experience in deep learning.

▪ Deployment understanding can work hand in hand with MLOps team.

▪ Understanding/working experience of Recommendation systems.

Good to have

▪ Experience in MLOps, CI/CD pipelines.

▪ Experience in Docker, Kubernetes

▪ Experience in using LLMs in RAG Framework

▪ Experience in E-commerce domain.

▪ Experience in Vector database and GenAI has context menu

About Us

Founded in 1956, Williams-Sonoma Inc. is the premier specialty retailer of high-quality products for the kitchen and home in the United States. Today, Williams-Sonoma, Inc. is one of the United States' largest e-commerce retailers with some of the best known and most beloved brands in home furnishings. Our family of brands are Williams-Sonoma, Pottery Barn, Pottery Barn Kids, Pottery Barn Teen, West Elm, Williams-Sonoma Home, Rejuvenation, GreenRow and Mark and Graham. We currently operate retail stores globally. Our products are also available to customers through our catalogs and online worldwide.

Williams-Sonoma has established a technology center in Pune, India to enhance its global operations. The India Technology Center serves as a critical hub for innovation and focuses on developing cutting-edge solutions in areas such as e-commerce, supply chain optimization, and customer experience management. By integrating advanced technologies like artificial intelligence, data analytics, and machine learning, the India Technology Center plays a crucial role in accelerating Williams-Sonoma's growth and maintaining its competitive edge in the global market

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About The Company

Maharashtra, India (On-Site)

Pune, Maharashtra, India (On-Site)

Pune, Maharashtra, India (On-Site)

Pune, Maharashtra, India (On-Site)

Pune, Maharashtra, India (On-Site)

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