Principal Engineer, Machine Learning Architecture

Position Overview

As a Principal Engineer, Machine Learning Architecture within Marqeta's Data+ML organization, you will be responsible for leading the technical vision and development of ML infrastructure. This infrastructure will support the end-to-end development and delivery of ML models at Marqeta. You will collaborate closely with Machine Learning Science, Product, and Engineering teams to refine ML development journeys, define our target state ML architecture, drive technical design decisions, and oversee implementation. This role also involves collaborating with engineering teams to promote best practices and enhance our operational posture. You will build strong working relationships with product and engineering leaders outside the Data+ML organization, mentor members of the Data+ML team, and contribute to the design and build-out of Marqeta's data and ML ecosystem.

This role reports directly to the Sr. Director of Machine Learning.

Location: Flexible First - Remote within the United States or from our Oakland, CA headquarters.

The Impact You'll Have

• Build a technical vision for our ML infrastructure optimized to support our customers and internal Machine Learning Scientists, aligning with our business and AI strategy.
• Create infrastructure to support end-to-end ML development and delivery, including prototyping, data and feature pipeline development, model training, deployment, and monitoring on AWS.
• Collaborate with Machine Learning Science, Product, and Engineering teams to define technical designs, integrations with our core products, and deliver highly available ML capabilities to our end-users.
• Maintain a high bar for operational excellence, drive best practices, and operate ML capabilities within established SLAs.
• Collaborate with key Product, Engineering, and Security stakeholders to drive governance, security, and management best practices, including standards, processes, and tools to improve our operating posture.
• Provide career mentorship and guidance to members of the Data+ML organization on topics including engineering skills, best practices, and business communication.

Who You Are

• Experience:
  • 10+ years in a Machine Learning engineering or architecture role with deep expertise in ML architecture, MLOps, feature stores, data pipelines, inference, and monitoring infrastructure using AWS managed services.
  • 10+ years of experience building large-scale, compliant ML architectures in the financial services or similarly regulated industry.
  • 10+ years of experience using product-oriented, user experience-centered approaches to building ML platforms and services.
• Skills:
  • Excellent communication and interpersonal skills, with the ability to cultivate relationships across teams, influence decision-making, and collaborate with stakeholders at all levels.
  • Proven ability to develop structure, advance execution, and measure performance within various and complex projects, teams, and environments.
  • Excellent verbal and written communication skills, including the ability to create technical design and product requirements documentation.
  • Proactive and strategic mindset, with the ability to anticipate business needs of customers and stakeholders.
  • Strong bias toward action and ability to operate proactively and effectively in a dynamic, fast-paced environment.
  • High ethical standards and a commitment to promoting a strong culture.
• Education: BS degree preferred.

Compensation And Benefits

• Flexible time off – take what you need.
• Retirement savings program with company contribution.
• Equity in a publicly-traded company and an Employee Stock Purchase Program.
• Health insurance premiums paid 100% + coverage for dependents and pets.
• Family-forming benefits including fertility support and up to 20 weeks of Parental Leave.
• Free therapy.