[Hiring] Machine Learning Engineer II @Kohl's

Role Description

In this role, you will focus on MLOps, supporting cross-functional teams 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

• Collaborate with Data Scientists and Engineers across the full ML lifecycle, including building and scaling ETL pipelines, deploying models into customer-facing applications, and enabling efficient model development through cloud infrastructure and tooling.
• Design, build, and maintain scalable machine learning infrastructure, including model serving (real-time and batch), training environments, and orchestration systems, with a focus on performance, scalability, and cost efficiency.
• Contribute to the roadmap for Machine Learning Engineering and Data Science tools, including developing reusable frameworks and standardized solutions to streamline model implementation.
• Partner with and support Data Scientists by enabling effective use of cloud-based tools and infrastructure, and providing technical expertise across the ML lifecycle.
• Collaborate with machine learning engineers to share knowledge, improve best practices, and foster a culture of continuous learning and development.
• Support development and maintain monitoring, alerting, and automated testing frameworks to ensure the reliability, performance, and integrity of data pipelines, models, and infrastructure.
• Develop, document, and communicate implementations and best practices across the data science lifecycle.
• Manage and communicate cloud infrastructure costs and budgets to project stakeholders.
• Stay current with GCP services and evolving best practices in Machine Learning Engineering and MLOps.
• Additional tasks may be assigned.

Qualifications

• Experience in MLOps or DevOps 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.
• Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics or equivalent quantitative field.
• Experience working with Data Scientists to deploy, scale, and operationalize machine learning models in production environments.
• 3+ years of experience as a Machine Learning Engineer with a proven track record of successful project delivery.
• 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.

Requirements

• Master’s Degree (Preferred).
• Proficiency in Java or other languages (Preferred).
• Retail experience (Preferred).
• E-commerce experience (Preferred).
• 5+ years of experience in Machine Learning (Preferred).
• Experience with optimization techniques and tools (e.g., Gurobi, linear programming, mixed-integer programming) (Preferred).
• Experience working with agent-based or agentic AI systems, including orchestration of autonomous workflows or LLM-driven agents (Preferred).

Essential Functions

• 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 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.