Staff Machine Learning & Intelligent Automation Engineer

At Niagara, we’re looking for Team Members who want to be part of achieving our mission to provide our customers the highest quality most affordable bottled water.

Consider applying here, if you want to:   

• Work in an entrepreneurial and dynamic environment with a chance to make an impact.   
• Develop lasting relationships with great people.   
• Have the opportunity to build a satisfying career.

We offer competitive compensation and benefits packages for our Team Members.

Staff Machine Learning & Intelligent Automation Engineer

The Enterprise Machine Learning & Intelligent Automation Staff Engineer is a senior technical team member responsible for designing, deploying, and scaling AI and ML driven solutions that directly power enterprise business initiatives. This role focuses on applying machine learning models, intelligent automation, and advanced analytics to real-world business problems, enabling smarter, faster, and more autonomous decision-making across the organization. The Staff Engineer serves as a technical authority for ML solution design, model integration, and AI automation patterns, bridging data science, data engineering, and business teams to operationalize models into production ready systems. This role emphasizes practical ML applications, AI platform enablement, and intelligent process automation rather than experimental research.

Essential Functions

• Define Lead the design and delivery of end-to-end machine learning solutions that support enterprise business initiatives.
• Architect scalable ML pipelines including feature engineering, model training, evaluation, deployment, and monitoring.
• Translate business problems into ML-driven solution architectures with clear success metrics and outcomes.
• Define reusable ML solution patterns and reference architectures for enterprise adoption.
• Serve as a technical escalation point for complex ML and AI solution challenges.
• Design and implement intelligent automation solutions leveraging ML models, AI services, and orchestration frameworks.
• Enable AI-driven process automation, decision automation, and predictive workflows across business functions.
• Integrate ML models with enterprise systems, BI platforms, APIs, and automation tools (RPA/BPA).
• Identify opportunities to replace manual or rules-based processes with ML-powered automation.
• Lead model operationalization practices including CI/CD for ML, versioning, monitoring, and retraining strategies.
• Establish MLOps standards covering model performance, explainability, drift detection, and reliability.
• Partner with platform and data engineering teams to ensure scalable, secure, and compliant ML infrastructure.
• Ensure ML solutions meet enterprise standards for security, governance, and regulatory compliance.
• Collaborate with data engineering teams to ensure data pipelines support ML feature generation and model consumption.
• Design and maintain feature stores, training datasets, and inference data flows.
• Ensure data quality, lineage, and observability for ML-critical data assets.
• Guide data modeling and transformation decisions to optimize ML performance.
• Serve as a Staff-level technical leader across AI, ML, automation, and data domains.
• Mentor ML engineers, data scientists, and automation engineers on best practices and solution design.
• Influence enterprise AI strategy, use case prioritization, and platform roadmaps.
• Evaluate emerging ML, GenAI, and automation technologies for enterprise applicability.
• Promote responsible AI, model transparency, and ethical AI practices.

Qualifications

• Minimum Qualifications:
  • 6+ years of experience in machine learning engineering, data science, AI engineering, or related fields.
  • 6+ years delivering production ML solutions supporting business or operational use cases.
  • 6+ Hands-on experience deploying and integrating ML models into enterprise systems.

*experience may include a combination of work experience and education

• Preferred Qualifications:
  • 10+ years of experience in ML engineering, AI platforms, or intelligent automation.
  • 10+ Experience delivering AI-powered automation or decision-intelligence solutions.
  • 10+ Experience mentoring ML or AI engineering teams.
  • 10+ Experience working with Generative AI or large language models in applied use cases.

*experience may include a combination of work experience and education

Competencies