ML/ Optimization Engineer (P1607)

We are a community of analysts that act as the voice of the customer – they share their story with us each and every day. Through simple, comprehensive, purposeful analytics, we fearlessly bring these customer stories and journeys to life. Our 360° customer view allows us to anticipate customer needs, thus enabling our clients to connect with their customers in meaningful, relevant ways. 

The Stores, Assortment, and Space (SAS) team is looking for a Senior ML Engineer to join the team. This role will focus on developing technical solutions to support assortment decision-making at Kroger, building packages and tools that will enable reliable and efficient execution and delivery of 84.51°’s best-in-class assortment data and sciences to internal and external stakeholders. The ideal candidate for this role should have strong technical skills and be comfortable collaborating cross-functionally with data scientists and data engineers to develop advanced analytical methods and scale them in production. 

RESPONSIBILITIES:  

• Experience implementing and evolving MLOps best practices
• Data engineering, automating ML workflows, experiment tracking, model registration, accuracy monitoring, model serving.  
• Evolve or develop methodologies and solutions for assortment and space optimization  
• Special focus is on item performance prediction models and optimization algorithms.
• Effective alignment of stakeholders and deliverables using documentation to ensure on-time delivery and acceptable output.
• Support the technical development of foundational assortment sciences and data products end-to-end, including documentation, CI/CD deployments, and input/output QA checks
• Identifying opportunities for standardization & automation of existing solutions and processes.
• Working closely with key internal stakeholders to ensure SLA’s are met for model pipeline; output accuracy is consistent, reliable, and reproducible.
• Partner with other technical experts (i.e. engineering, architecture) to identify and implement best practices in tech stack, tool usage, and code development. 

QUALIFICATIONS, SKILLS, AND EXPERIENCE:  

• 2+ years of experience using Python or Pyspark to develop analytical solutions.
• 2+ years of experience with big data tools, and architecture (e.g. Kubernetes, Spark).
• 2+ years of experience with data wrangling/cleaning/prep.
• Experience with cluster specification and query execution optimization in Databricks. 
• Experience building or maintaining modular applications, pipelines, packages, or libraries.
• Passionate about technical solution development and code management best practices. 
• Demonstrates grit when solving complex and drawn-out methodological or scaling issues.
• Ability to work in a highly collaborative environment.
• Strong academic background in computer science, engineering, or similar discipline.
• Experience with neural networks a plus
• Grocery and/or retail experience is a plus. 

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