Your OpportunityAt Schwab, you're empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us challenge the status quo and transform the finance industry together. We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s).
As an AI Researcher within Schwab's Artificial Intelligence Strategy & Transformation (AI.x) organization, you'll operate at the intersection of advanced applied research and production-grade AI systems that support millions of investors, advisors, and employees. This role is designed for researchers who want their work to ship, scale, and deliver measurable impact in real environments-where latency, reliability, cost, and regulatory considerations matter as much as model performance.
In this role, you'll take ideas from early problem formulation through modeling, evaluation, deployment, and iteration, contributing directly to LLM and Agentic-based systems used across the enterprise. Your work will include designing and operating large-language-model-based and agent-driven systems, establishing robust evaluation and monitoring practices, and improving performance under real-world constraints. You'll collaborate closely with platform engineers, product partners, and risk stakeholders to ensure solutions are accurate, observable, safe, and reliable in a regulated financial services environment.
Success in this role is measured by production impact and sustained system quality-not novelty alone. Over time, your contributions will help shape Schwab's AI standards and best practices, influence how AI is responsibly deployed at scale, and strengthen the firm's long-term AI capabilities.
This is a hybrid role based in San Francisco, CA, with regular in-office collaboration to support complex technical work.
What you haveRequired Qualifications- Master's degree or higher in Computer Science, Machine Learning, Mathematics, Physics, or a related field, or equivalent practical experience.
- 7+ years of experience building, deploying, and operating machine learning or AI systems using Python in production environments.
- Demonstrated experience delivering GenAI or LLM-powered applications that are actively used by clients or internal teams.
- Strong grounding in data analysis (Python, SQL, Pandas), experimentation, and evaluation, with the ability to assess model quality, reliability, and trade-offs under real constraints.
- Experience working cross-functionally with engineering, product, and other stakeholders to move complex technical work from concept to production.
Preferred Qualifications- Experience designing or operating agentic-based or orchestrated AI systems, including tool-enabled or multi-step workflows.
- Familiarity with AI evaluation, monitoring, or reliability practices that support long-running production systems.
- Experience operating AI solutions in regulated, high-stakes, or risk-sensitive environments.
- Technical leadership or mentoring experience, including influencing standards, patterns, or best practices across teams.
In addition to the salary range, this role is also eligible for bonus or incentive opportunities.
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