About The Position

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.

Requirements

  • 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
  • Strong understanding of supervised, unsupervised, and reinforcement learning techniques.
  • Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn, or equivalent).
  • Experience operationalizing models for batch and real-time inference.
  • Knowledge of model evaluation, bias mitigation, and explainability techniques.
  • Experience building MLOps pipelines including model CI/CD, monitoring, and retraining.
  • Familiarity with orchestration tools, workflow automation, and RPA/BPA platforms.
  • Strong understanding of API-based ML integration and event-driven architectures.
  • Strong SQL and Python programming skills.
  • Experience with cloud AI/ML platforms (AWS, Azure, GCP, Databricks, Snowflake).
  • Understanding of data engineering fundamentals and distributed data processing.
  • Strong systems thinking and solution architecture capabilities.
  • Ability to influence AI and automation strategy across the enterprise.
  • Strong communication skills translating ML concepts into business value.
  • Demonstrated ability to mentor and lead without formal authority.
  • Bachelor's Degree in Computer Science, Data Science, Engineering, Artificial Intelligence, or related field.

Nice To Haves

  • 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
  • Cloud AI/ML certifications (AWS, Azure, or GCP)
  • Databricks, Snowflake, or ML platform certifications
  • AI, Machine Learning, or MLOps certifications
  • Master's Degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or related field.

Responsibilities

  • 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.

Benefits

  • Paid Time Off for holidays, sick time, and vacation time
  • Paid parental and caregiver leaves
  • Medical, including virtual care options
  • Dental
  • Vision
  • 401(k) with company match
  • Health Savings Account with company match
  • Flexible Spending Accounts
  • Expanded mental wellbeing benefits including free counseling sessions for all team members and household family members
  • Family Building Benefits including enhanced fertility benefits for IVF and fertility preservation plus adoption, surrogacy, and Doula reimbursements
  • Income protection including Life and AD&D, short and long-term disability, critical illness and an accident plan
  • Special discount programs including pet plans, pre-paid legal services, identity theft, car rental, airport parking, etc.
  • Tuition reimbursement, college savings plan and scholarship opportunities
  • And more!
  • https://careers.niagarawater.com/us/en/benefits
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