Senior AI/ML Engineer, Client Authentication

real-time and batch data pipelines. This role is ideal for someone who can design production-grade ML systems end-to-end: from data ingestion and feature engineering to model deployment, monitoring, and business decision integration.

You'll work at the intersection of data architecture and AI, engineering resilient pipelines that enable advanced analytics and machine-learning models at scale. This is a hands-on, end-to-end engineering role where your work directly supports teams protecting clients and strengthening trust across the firm.

Key Responsibilities

• Design and build ML pipelines that combine streaming events and batch processing

• Develop, deploy, and optimize models for risk scoring in user login, transactions and payment journeys

• Create robust feature engineering pipelines and reusable feature definitions for both online and offline use

• Integrate model outputs into operational decision systems

• Implement MLOps best practices in standardizing the entire machine learning lifecycle

• Improve data quality and reliability through schema governance, deduplication, lineage, and data validation checks

• Partner with risk analysts and product stakeholders to convert business rules and feedback into model improvements

• Contribute to analytics, dashboards, and LLM-assisted tooling that helps teams understand fraud patterns and model behavior

What you have

Required Qualifications

• 8+ years of professional experience in software, data, or machine learning engineering

• 3-4+ years of hands-on AI/ML experience building and deploying ML models in production

• Advanced Python and SQL skills with deep BigQuery experience in large-scale data processing

• Proven experience with both real-time and batch pipeline design

• Demonstrated ability to own data preparation and quality

• Strong understanding of feature engineering

• Experience with cloud ML and data platforms for model training/deployment, data warehouse and orchestration

• Experience integrating ML models into low-latency production systems for real time insights and decisioning

Preferred Qualifications

• Master's or advanced degree in computer science or a related field

• Experience with event-driven architectures and streaming platforms such as Kafka or Pub/Sub

• Experience applying GenAI/LLM capabilities to analytics workflows

• Experience applying advanced analytical techniques such as graph analytics, anomaly detection, entity linking for pattern detection

• Hands-on experience with GCP ML services

• Experience working in regulated environments with audit, compliance, and model governance requirements

• Prior experience in fraud, risk, or financial crime analytics

In addition to the salary range, this role is also eligible for bonus or incentive opportunities.

What's in it for you

At Schwab, you're empowered to shape your future. We champion your growth through meaningful work, continuous learning, and a culture of trust and collaboration-so you can build the skills to make a lasting impact. Our Hybrid Work and Flexibility approach balances our ongoing commitment to workplace flexibility, serving our clients, and our strong belief in the value of being together in person on a regular basis.

We offer a competitive benefits package that takes care of the whole you - both today and in the future:

• 401(k) with company match and Employee stock purchase plan
• Paid time for vacation, volunteering, and 28-day sabbatical after every 5 years of service for eligible positions
• Paid parental leave and family building benefits
• Tuition reimbursement
• Health, dental, and vision insurance