Senior Machine Learning Engineer in Raceland

Job DescriptionJob Description

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 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, , veterans and disabled individuals, and without regard to and .