Harley-Davidson Motor Company · 19 hours ago
Senior ML/GenAI Ops Engineer
Milwaukee, WI
Full-time
Onsite
Senior Level
$100K/yr - $155K/yr
7+ years expHarley-Davidson is a storied brand committed to innovation and adventure, and they are seeking a Senior ML/GenAI Ops Engineer to join their team. This role involves designing, developing, and operationalizing machine learning and generative AI platforms to deliver impactful business solutions while ensuring scalability and compliance.
AutomotiveBusiness DevelopmentIndustrialManufacturingTransportation
No H1B
Responsibilities
Design, develop, and maintain scalable platforms for machine learning and GenAI, supporting end-to-end processes from data ingestion to model deployment and monitoring
Lead end-to-end solution design for ML/AI data pipelines and model-serving platforms, ensuring architectures meet scalability, reliability, and regulatory requirements
Partner closely with project and program managers to establish delivery timelines, resource plans, and milestone tracking for complex, multi-team data/ML efforts
Champion best practices for reproducibility, automation, observability, and governance/COE in ML/AI operational pipelines and platforms
Oversee compute governance, alert monitoring and model lifecycle
Implement CI/CD pipelines for automated deployment of ML and AI models to production environments
Work closely with data scientists to ensure model readiness and optimization, focusing on robust deployment and monitoring
Develop and manage tools for continuous monitoring and performance management of models post-deployment to identify and resolve performance drift
Partner with data scientists, software engineers, product owners, and stakeholders to align ML and AI solutions with business goals and performance metrics
Facilitate seamless integration of ML/AI systems with business processes, ensuring data accessibility, quality, and real-time insights
Ensure systems are built for scalability, maintainability, and security, adhering to best practices in ML & AI DevOps
Implement monitoring solutions to proactively address any issues in data, model performance, or infrastructure
Drive architectural reviews, design decisions, and engineering standards that support long-term operational excellence for ML/AI workloads
Serve as the primary technical escalation point for delivery risks and system performance issues, ensuring timely resolution and stakeholder alignment
Integrate AI ethics and compliance considerations into all ML/AI solutions, with a focus on data privacy, bias detection, and model transparency
Implement processes to meet regulatory requirements and promote responsible AI use
Qualification
Required
High School Diploma or Equivalent Required
7+ years of experience in data engineering or DevOps 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
Proficiency in Azure Cloud Platform, specifically Azure ML Studio and Azure AI Foundry
Proficiency in Python, SQL, and ML/AI DevOps tools (e.g., MLflow, scikit learn, PyTorch, Kubeflow, TensorFlow Extended)
Experience with CI/CD tools (e.g., Jenkins, GitLab CI) and containerization/orchestration tools (Docker, Kubernetes)
Familiarity with machine learning frameworks (e.g., TensorFlow, 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
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 enforce data privacy, lineage, and data quality controls across ML workflows, ensuring compliance with enterprise and regulatory requirements
Preferred
Bachelor's or Master's degree in Computer Science, Data Engineering, Machine Learning, or a related field is preferred
Azure AZ-900 certification, with additional ML/LLM/RAG focused certifications preferred
Benefits
Annual bonus programs
Health insurance benefits
A 401k program
Onsite fitness centers
Employee stores
Employee discounts on products and accessories
Company
Harley-Davidson Motor Company
In 1903, out of a small shed in Milwaukee, Wisconsin, four young men lit a cultural wildfire that would grow and spread across geographies and generations.
5001-10000 employees
Funding
Current Stage
Public CompanyTotal Funding
$89MKey Investors
US Department of Energy
2024-07-11Grant· $89M
1986-07-18IPO
Leadership Team
Arthur Starrs
President and CEO at Harley-Davidson
Bill Davidson
Special Advisor to the CEO
Recent News
2026-01-16
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2026-01-16
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