Job Title: Senior Machine Learning Engineer
Location: Mulitple Locations
Position Overview:
The Senior ML Engineer is responsible for operationalizing machine learning and AI solutions into scalable, reliable, and production-ready enterprise systems. This role bridges data science, software engineering, and infrastructure disciplines to deploy, monitor, optimize, and support AI solutions that drive operational and business outcomes.
Key Responsibilities:
Deploy, integrate, and maintain machine learning and AI solutions within enterprise workflows and operational systems
Design and develop scalable ML pipelines, feature stores, APIs, and model-serving infrastructure
Collaborate with Data Scientists to productionize models and improve deployment readiness
Monitor model performance, drift, availability, and reliability across production environments
Implement processes for model retraining, versioning, governance, and lifecycle management
Partner with Data Engineering teams to support feature engineering and data pipeline integration
Ensure ML solutions are secure, scalable, maintainable, and aligned with enterprise architecture standards
Support AI applications across forecasting, operational optimization, bidding, scheduling, maintenance, and automation use cases
Troubleshoot and resolve issues related to model deployment and operational performance
Contribute to ML engineering standards, best practices, and platform improvements
Document architecture, deployment processes, and operational support procedures
Qualifications:
Bachelor's degree in Computer Science, Software Engineering, Data Science, or related field
6-10 years in ML or software engineering
Strong Python and ML deployment experience
Experience with cloud ML systems
Skills:
Experience with Azure ML, Databricks, ML Ops, or similar cloud AI platforms
Experience in manufacturing, industrial, operational, or engineering environments
Familiarity with large language models, Generative AI, and intelligent automation
Experience supporting enterprise AI applications integrated with ERP or operational systems
Knowledge of monitoring, observability, and model governance practices
Experience with Docker, Kubernetes, and infrastructure-as-code practices
Bollinger is an equal opportunity employer and is committed to providing employment opportunities to minorities, females, veterans and disabled individuals, and without regard to sexual orientation and gender identity.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 80184442
- Position Id: 9f96c4694596616feae189b76e365856
- Posted 4 days ago
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