Principal ML/AI Engineer

About the Role

A position at White Cap isn’t your ordinary job. You’ll work in an exciting and diverse environment, meet interesting people, and have a variety of career opportunities. The White Cap family is committed to Building Trust on Every Job by being deeply knowledgeable, fully capable, and always dependable. As the senior technical leader for machine learning (ML) and artificial intelligence (AI), you will design, develop, and operationalize ML/AI solutions addressing complex business challenges while establishing technical standards and architectural direction for the team. This role accelerates delivery, elevates engineering quality, and strengthens team capabilities through hands-on technical leadership, mentorship, and support.

Responsibilities

• Serve as the principal engineering authority for enterprise-grade systems supporting data science, machine learning, and AI in Azure and Databricks.
• Set the technical direction and architectural patterns to turn analytical models and prototypes into production solutions that are scalable, secure, reliable, and maintainable.
• Lead the architecture and hands-on development of applications, services, APIs, and reusable components delivering data science solutions, covering model execution, business workflows, user experiences, system integrations, and downstream consumption of model outputs.
• Design systems to scale across users, datasets, models, and business processes. Own tradeoffs related to performance, fault tolerance, availability, security, maintainability, and cost, and surface architectural risks early to support long-term enterprise use.
• Establish engineering practices for deploying, operating, and monitoring ML/AI solutions in production. Define standards for CI/CD, automated testing, model and code versioning, environment management, observability, rollback, and production support across the full solution lifecycle.
• Define and enforce software engineering standards for teams building systems in support of data science.
• Lead architecture, design, and code reviews covering code quality, modularity, testing, documentation, security, and maintainability. Serve as the final escalation point for complex technical decisions.
• Mentor engineers supporting data science and AI initiatives, guide them through complex implementation challenges, promote engineering best practices, and build the team's depth in cloud architecture, software development, distributed systems, and MLOps.
• Partner 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.
• Translate analytical requirements into engineering designs and communicate technical decisions, dependencies, risks, and tradeoffs clearly.

Scope and Impact

• Consult with senior management on solution development for complex strategic and technical business issues.
• Independently solve unique and complex problems with broad business impact.
• Establish operational plans for assigned areas and act as a strategic advisor using expert skills to contribute to the development of company objectives.
• Guide and mentor staff at all levels, provide advice to senior management on complex issues, and lead or manage projects with dotted-line responsibility.

Work Environment

Located in a comfortable indoor area with infrequent unpleasant conditions. Most of the time is spent sitting with frequent opportunities to move about. Rare occasions may require moving or lifting light articles. Typically requires overnight travel less than 10% of the time.

Qualifications

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

Preferred Qualifications

• Advanced degree in computer science.
• Strong ability to summarize and communicate technical challenges and solutions effectively.

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