Principal / Staff Machine Learning Engineer

Role Overview

• Architect and maintain the machine learning deployment framework used to operationalize models and decisioning engines.
• Partner with stakeholders to define business use cases, success criteria, and project timelines, and own requirements gathering, solution design, deployment strategy, and performance tracking for data science deployments.
• Design, build, and manage batch and real-time machine learning pipelines to support deployment of models, decision frameworks, and optimization engines.
• Collaborate with Data and Decision Science team members to build feature libraries, feature stores, feedback loops, and reusable components that streamline model development, validation, and deployment.
• Own operational governance of the model lifecycle, including model versioning, promotion, rollback, deprecation, and ongoing monitoring for production machine learning systems.
• Develop and optimize cloud-based data architectures for scalability, low latency, reliability, and cost efficiency, implementing robust data quality controls, validation checks, test coverage, monitoring, and alerting for production-grade pipelines and data products.
• Deploy data and analytics solutions to Amazon Web Services (AWS) using CI/CD automation and DevOps best practices, and maintain clear technical documentation while collaborating within Agile workflows using tools such as JIRA and Confluence.
• Conduct analytics and support development of machine learning and predictive model pipelines and frameworks that advance credit risk and fraud strategies.

Requirements

• 6 years of experience in machine learning engineering, data engineering, or data science, designing and building production-grade data or ML pipelines in a commercial environment.
• 6 years of experience developing and optimizing data solutions on cloud platforms, including hands-on experience with AWS capabilities and Snowflake in an engineering context, along with production use of machine learning pipelines, feature stores, or MLOps practices.
• 6 years of experience creating Python microservices, working with containers, and developing application programming interfaces (APIs) to support data and machine learning solutions.
• 6 years of experience collaborating with internal and external stakeholders and driving initiatives using clear, effective verbal and written communication skills.
• 6 years of experience building scalable, low-latency systems or feature components that support analytics, machine learning, or decisioning use cases.
• 6 years of experience with CI/CD automation and DevOps practices to deploy, monitor, and support data solutions in production environments.
• Bachelor’s degree or higher in Mathematics, Statistics, Computer Science, Engineering, or a related quantitative field, or equivalent combination of education, related experience and/or military experience.

Tech Stack

• AWS
• Cloud
• Microservices
• Python

Benefits

• Fuel Your Life program to support your physical, financial, social, and emotional well-being.
• Paid holidays and generous time away policies.
• No-cost mental health support through Employee Assistance Programs.
• Living Proof program to recognize your peers’ extra effort with points redeemable for rewards.
• Eight Employee Resource Groups to foster a collaborative culture and expand your network.
• Unparalleled professional growth with training, development, and internal mobility opportunities.
• Medical, dental, vision, life, and disability insurance options available from day one.
• Retirement planning and discounted shares with the Employee Stock Purchase Plan.
• Tuition assistance and reimbursement program.
• Paid parental, caregiver, and military leave.