Principal ML/AI Engineer

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Job Summary

Responsible for serving as the Data Science team's senior technical leader and subject matter expert for machine learning (ML) and artificial intelligence (AI) systems. Responsible for the design, development, and operationalization of machine learning and AI solutions that address the organization's most complex business challenges while establishing technical standards and architectural direction for the team. As a force multiplier, this role accelerates delivery, elevates engineering quality, and strengthens team capabilities through hands-on technical leadership, mentorship, and support.

Major Tasks, Responsibilities and Key Accountabilities

• Serves as the principal engineering authority for enterprise-grade systems supporting data science, machine learning, and AI in Azure and Databricks. Sets the technical direction and architectural patterns that turn analytical models and prototypes into production solutions that are scalable, secure, reliable, and maintainable.

• Leads the architecture and hands-on development of applications, services, APIs, and reusable components that deliver and operate data science solutions, covering model execution, business workflows, user experiences, system integrations, and downstream consumption of model outputs.

• Designs systems to scale across users, datasets, models, and business processes. Owns the tradeoffs related to performance, fault tolerance, availability, security, maintainability, and cost, and surfaces architectural risks early so solutions support long-term enterprise use.

• Establishes the engineering practices for deploying, operating, and monitoring ML/AI solutions in production. Defines standards for CI/CD, automated testing, model and code versioning, environment management, observability, rollback, and production support across the full solution lifecycle.

• Defines and enforces software engineering standards for teams building systems in support of data science.

• Leads architecture, design, and code reviews covering code quality, modularity, testing, documentation, security, and maintainability, and serves as the final escalation point for complex technical decisions.

• Mentors engineers supporting data science and AI initiatives and guides them through complex implementation challenges, promotes engineering best practices, and builds the team's depth in cloud architecture, software development, distributed systems, and MLOps.

• Partners with data scientists, data engineers, product teams, enterprise architects, information security, infrastructure teams, and business stakeholders to ensure data science solutions are built on appropriate software and platform architectures.

• Translates analytical requirements into engineering designs and communicates technical decisions, dependencies, risks, and tradeoffs clearly.

Nature and Scope

• Consults with senior management on solution development for complex strategic and technical business issues. Independently solves unique and complex problems that have a broad impact on the business. Assignments are large scope, high impact, high cost, and high importance.

• Establishes operational plans for assigned area. Acts as a strategic advisor and uses expert skills to contribute to the development of strategic company objectives. Receives general administrative and business direction as needed. Typically operates with broad latitude in a complex environment.

• Guides and mentors staff at all levels, provides advice to senior management on complex and strategic issues, and may lead or manage complex projects with dotted line responsibility.

Work Environment

• Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

• Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.

• Typically requires overnight travel less than 10% of the time.

Education and Experience

• Typically requires a bachelor’s degree and 10+ years of experience in a related field OR MS/MA and generally 8+ years of experience in a related field. Maintains expert knowledge in area of responsibility with a strong understanding in adjacent areas for the development of creative solutions.

Preferred Qualifications

• Advanced degree in computer science.

• Strong ability to summarize and communicate technical challenges and solutions effectively.

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