ML/AI Ops Engineer

Neiman Marcus
Irving, Texas, United States
27 May 2022
09 Sep 2022

Neiman Marcus Group (NMG) has been the premier destination for luxury fashion and goods, superior service, and an elevated retail experience for more than a century. Today, 9,000 associates contribute to the success of NMG's brands: Neiman Marcus, Bergdorf Goodman, Last Call, and Horchow. There are 38 full-line Neiman Marcus stores in cosmopolitan markets across the United States and a sophisticated digital platform that attracts shoppers worldwide. Bergdorf Goodman operates two stores in landmark locations on Fifth Avenue in New York City and, catering to loyal luxury customers globally. NMG also owns five Last Call stores and, an e-commerce site that offers premium furniture and home decor.

As an organization, NMG is on a transformational journey to become the preeminent luxury customer platform. NMG continues to deliver the best integrated customer experience and has evolved the business to succeed in the ever-changing retail landscape. NMG is a relationship business. What differentiates the organization from other luxury retailers are its unique assets: a strong store footprint, the most knowledgeable associates, an engaging online experience, solid brand partnerships, innovative digital and in-store experiences, the most loyal luxury customer base, and a strong balance sheet.

Our customers will always be at the center of everything NMG does. The company continues to reinvest in new technologies that enhance the customer experience. NMG meets customers where they are. NMG's goal is to offer customers a seamless experience across its stores, online, and remote digital selling.

NMG's priority is to develop a highly engaged and high-performing team where everyone belongs. The business attracts and retains best-in-class talent through unique offerings provided to associates in addition to standard employer benefits. These include an innovative way of working, associate discounts on merchandise, tuition reimbursement, associate hardship fund, and paid time off to volunteer, to name a few.

As part of NMG's Environmental, Social, Governance (ESG) work, the organization is focused on driving its core value of being "All Heart." NMG is also assessing its current environmental and social impact while developing a three-year plan to lead the luxury industry in its commitment and transparency to environmental and social sustainability. NMG strives to become an employer of choice, driven by a culture of Belonging. A dedicated team focuses on this journey, directly impacting how NMG conducts business throughout the workforce, workplace, and marketplace dimensions.

NMG has incredibly passionate and committed corporate and store associates. NMG offers associates an environment where everyone feels welcomed, nurtured, and empowered. Our associates are the heart of NMG. As an organization, NMG leads with love - love for customers, love for associates, and love for brand partners.


We are looking for an ML/AI Ops Engineer to transform our data science development lifecycle and data creation pipelines to production quality. This person will have a strong computer science background and be excited to embed best coding practices into a growing data science team. They should be equally comfortable with data preparation and analysis as they are with the deployment of enterprise scale models into a production environment. They will build re-usable tools supporting model evaluation and data creation. We are looking for someone who sees the forest through the trees and is comfortable creating a solution to a business problem without needing someone to provide the details of how to implement the solution.

Job Requirements:
  • 2+ years' experience working in ML Ops or similar role
  • 1+ years' experience with Spark
  • 1+ years' experience working as a hands-on data scientist
  • Strong coding skills in python and SQL
  • Skilled at the AWS suite
  • Experience with SDLC, best coding practices, and experimental design methodologies
  • Experience designing, implementing, validating, and updating ETL pipelines
  • Bachelor's degree in STEM or related fields from an accredited university. Graduate degree preferred.
  • Strong statistical background
  • Comfort working on multiple projects concurrently
  • Experience building robust re-usable software tools

Who you are:
  • Extremely comfortable with scalable, repeatable, automated data science coding/computer science practices
  • Proficiency in large-scale distributed systems (preferably Spark)
  • Experience in supporting machine learning models with varying size and complexity
  • Skilled with the AWS suite
  • Advanced proficiency in Python and SQL
  • Solid understanding of statistics, algorithms, and data science models
  • Great communicator with strong collaborative skills

Job responsibilities:
  • Design and implement machine learning lifecycle
  • Create and maintain efficient data pipeline architecture
  • Develop resources that enable data scientists to rapidly develop, train, evaluate, and iterate machine learning models
  • Identify, optimize, and implement internal processes

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