Manager, Machine Learning Operations (Remote)

Role Specific Information Job Description About the Role As Manager, Machine Learning Operations (ML Ops), you will manage a team of engineers in designing, deploying, and operating machine learning solutions while building scalable infrastructure, tools, and best practices across the Machine Learning Engineering (MLE) ecosystem. What You’ll Do Attract, retain, develop, manage, coach and assess ML Ops Engineers Lead engineers on implementation of the full ML lifecycle, including building and scaling extract, transform, and load (ETL) pipelines, deploying Data Scientist developed models into customer-facing applications, and enabling efficient organizational throughput through cloud infrastructure and tooling Own the roadmap for Machine Learning Engineering and Data Science tools, including developing reusable frameworks and standardized solutions to streamline model implementation Research, prototype and instruct the team on creating cutting edge machine learning infrastructure Enable change for the team by moving decisions forward and eliminating blockers Provide technical thought leadership for Data Science managers on the topics of cloud-based tools and infrastructure for the ML lifecycle Instill best practices for your team and foster a culture of continuous learning and development, while training and coaching them through pair programming and code review Contribute to development, monitoring, alerting, and automated testing frameworks to ensure the reliability, performance, and integrity of data pipelines, models, and infrastructure Document, and communicate implementations and best practices to other leaders across Kohl’s broader data organization Stay current with Google Cloud Product (GCP) services and evolving best practices in MLE and ML Ops Additional tasks may be assigned What Skills You Have Required Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics or equivalent quantitative field 5+ years of experience as a Machine Learning Engineer with a proven track record of successful, independent, project delivery 2+ years of managerial or leadership experience in Data Science or Analytics organizations Expertise in ML Ops practices, including building and operating production ML systems using Docker, Kubernetes, CI/CD pipelines, Git-based version control, API development, model serving (batch and real-time), and automated testing frameworks Experience working with Data Scientists to deploy, scale, and operationalize machine learning models in production environments In-depth knowledge of cloud platform, preferably Google Cloud Platform services, particularly Vertex AI, BigQuery and Dataproc. Extensive expertise with CI/CD and IaC best practices Extensive knowledge of distributed computing and big data technologies like Spark, Kubeflow, Airflow and SQL Extensive expertise in Python and machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn) Experience working in Agile environments with an emphasis on iterative development and continuous delivery Preferred Master’s Degree Proficiency in Java or other languages Retail and E-Commerce experience 7+ years of experience in Machine Learning Experience with optimization techniques and tools (e.g., Gurobi, linear programming, mixed-integer programming) Experience working with agent based or agentic AI systems, including orchestration of autonomous workflows or LLM-driven agents Essential Functions The requirements listed below are representative of functions you will be required to perform, however you may be required to perform additional functions. Kohl’s may revise this job description at any time. To perform this job successfully, you must be able to perform each essential function satisfactorily. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions, absent undue hardship. Ability to perform the accountabilities listed in the “What You’ll Do” Section Ability to comply with dress code requirements Basic math and reading skills, legible handwriting, and basic computer operation Ability to maintain prompt and regular attendance and meet scheduling requirements as set by the company Ability to learn and comply with all company policies, procedures, standards and guidelines Ability to give direction and to receive, understand and proactively respond to direction from leadership and other company personnel Ability to work as part of a team and interact effectively and appropriately with others Ability to maintain composure and work in a fast paced environment while accomplishing multiple tasks within established timeframes Ability to satisfactorily complete company training programs Ability to use a personal computer for tasks such as communicating, preparing reports, etc. Ability to plan, prioritize and monitor activities across business units Ability to complete or oversee the completion of assigned projects in a timely manner