Principal Machine Learning Engineer

Job Title

Principal Machine Learning Engineer

Job Description Summary

We are seeking a Principal ML Engineer to build and maintain artificial intelligence and machine learning systems for our business. This role combines deep technical execution with broad influence: tackling the most complex machine learning problems, designing and implementing data architectures/models, MLOps and LLMOps, and monitoring and optimization as key software, while raising the bar for engineering excellence across the Data Organization.

Reporting to the Senior Director, Data Science & AI, the Principal ML Engineer is expected to move fluidly across project/product teams — embedding in projects for days or months at a time to unblock, accelerate, and uplift delivery. They will mentor other engineers at every level, push standards for technical excellence, and help establish the ML engineering, and architectural principles that guide our work.

The primary platform is Databricks and the Azure cloud ecosystem, with the expectation of evaluating and adopting additional data technologies as the platform evolves.

Job Description

We are seeking a Principal ML Engineer to build and maintain artificial intelligence and machine learning systems for our business. This role combines deep technical execution with broad influence: tackling the most complex machine learning problems, designing and implementing data architectures/models, MLOps and LLMOps, and monitoring and optimization as key software, while raising the bar for engineering excellence across the Data Organization.

Reporting to the Senior Director, Data Science & AI, the Principal ML Engineer is expected to move fluidly across project/product teams — embedding in projects for days or months at a time to unblock, accelerate, and uplift delivery. They will mentor other engineers at every level, push standards for technical excellence, and help establish the ML engineering, and architectural principles that guide our work.

The primary platform is Databricks and the Azure cloud ecosystem, with the expectation of evaluating and adopting additional data technologies as the platform evolves.

AI/ML Model Development

• Demonstrable experience shaping the end-to-end architecture, development, and deployment of AI, including machine learning, GenAI, and Agentic models that are tailored to business use cases.

• Design and develop agentic AI systems — including multi-agent orchestration, tool-use, evaluation, and autonomous task-execution pipelines — to automate complex enterprise workflows.

• Enforce model development standards encompassing data preprocessing, feature engineering, model selection, hyperparameter tuning, evaluation, and documentation.

• Partner with data engineering teams to ensure robust, scalable, and high-quality data pipelines that support model training and inference.

AI Operations (MLOps / LLMOps)

• Implement the organization's MLOps and LLMOps capabilities, including CI/CD pipelines for data wrangling, feature engineering, model training, evaluation, deployment, and monitoring.

• Help define and enforce standards for model versioning, experiment tracking, reproducibility, and model registry management.

• Implement robust model monitoring frameworks to detect performance degradation, data drift, concept drift, and bias in production systems, with automated alerting and retraining triggers.

AI Governance

• Implement AI governance frameworks, including policies for model risk management, fairness, explainability, privacy, and security.

• Champion sound AI principles across the global business, ensuring that human oversight and accountability are embedded in every stage of the AI development lifecycle.

• 10+ years bu…