Senior ML​/GenAI Ops Engineer - Milwaukee, WI

Senior ML/GenAI Ops Engineer
- Milwaukee, WI

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Title:

Senior ML/GenAI Ops Engineer
- Milwaukee, WI Job Function:
Digital

Location:

Juneau Workplace Category:
Onsite Company:
Harley-Davidson Motor Company Full or Part-Time:
Full Time Shift: SHIFT1

At Harley-Davidson, we are building more than machines. It's our passion and commitment to continue the evolution of this storied brand, and heighten the desirability of the Harley-Davidson experience. To keep building our legend and leading our industry through innovation, evolution, and emotion we need the best and brightest talent. We stand for the timeless pursuit of adventure. Freedom for the soul.

Are you ready to join us? Harley-Davidson Motor Company, founded in a humble Milwaukee backyard shed in 1903, still calls the city home. Today, its Corporate Campus includes a 4.8-acre public park—a welcoming green space open to all. Join our team as a Sr Data Engineer.

We are looking for a skilled Sr. Data Engineer - ML & AI Operations to join our growing team. In this role, you will be responsible for designing, developing, and deploying & operationalizing machine learning and generative AI (GenAI) platforms to deliver high-impact solutions to business challenges and optimize processes. This role focuses on the operationalization and automation of machine learning and AI solutions, ensuring they are seamlessly integrated into production environments with a high degree of scalability, reliability, and compliance with ethical guidelines.

The ideal candidate will bring strong technical expertise in data engineering, a deep understanding of ML and AI Dev Ops best practices, and a commitment to building robust, maintainable systems. You will lead the design, development, and scaling of data pipelines, ML infrastructure, and AI production systems that power models used across the business. If you are passionate about creating and operationalizing transformative ML and AI solutions, we'd love to hear from you!

• Platform Design & Development
• Model Deployment & Automation
• Collaboration and Business Alignment
• Operationalization & Maintenance
• Ethics and Compliance

High School Diploma or Equivalent Required Bachelor's or Master's degree in Computer Science, Data Engineering, Machine Learning, or a related field is preferred

7+ years of experience in data engineering or Dev Ops roles, with a focus on ML/AI platforms and infrastructure. Proven experience in operationalizing and automating ML and GenAI solutions in production environments. Strong experience with cloud platforms (AWS, Azure, GCP) and managing infrastructure for data and machine learning systems Azure AZ-900 certification, with additional ML/LLM/RAG focused certifications preferred.

Proficiency in Azure Cloud Platform, specifically Azure ML Studio and Azure AI Foundry Proficiency in Python, SQL, and ML/AI Dev Ops tools (e.g., MLflow, scikit learn, PyTorch, Kubeflow, Tensor Flow Extended). Experience with CI/CD tools (e.g., Jenkins, Git Lab CI) and containerization/orchestration tools (Docker, Kubernetes). Familiarity with machine learning frameworks (e.g., Tensor Flow, PyTorch) and data pipeline tools (e.g., Apache Airflow, dbt).

Proficiency with vector databases, LLM workflows, or RAG pipelines. Familiarity with cost management, autoscaling, and GPU governance in Azure ML. Experience with data governance frameworks and security best practices.

Technical Acumen:
Strong knowledge of ML/AI lifecycle management, MLOps practices, and data pipeline optimization. Collaboration & Communication:
Excellent teamwork skills with an ability to work closely with cross-functional teams and communicate complex technical concepts effectively. Help influence alignment across teams. Problem-Solving:
Proactive approach & proven ability to identifying and solve issues in model performance, data quality, and infrastructure bottlenecks. Ethics and Compliance:
Deep understanding of responsible AI practices, including bias detection, explainability, and data privacy. Governance & Data Integrity:
Ability to…