Senior AI Model Validation Engineer – Generative AI

Charles Schwab; Southlake (TX); Hybrid; USD 110,000 - 140,000; Full time

Benefits offered by this job

401(k) with company match

Sabbatical after 5 years

Paid parental leave

Tuition reimbursement

Health, dental, and vision insurance

Job summary

Charles Schwab is seeking an early‑career engineer or quantitative researcher to join the AI Model Validation team in a hybrid role (4 days in-office, 1 day remote) in Texas. You will validate AI/ML models, build testing frameworks, and present evidence-based conclusions to technical teams.

You'll work on generative AI, LLMs, and model governance with collaboration across developers, data scientists, risk teams, and leadership.

Qualifications

• Master's degree or Bachelor's with strong project/research experience in CS, data science, statistics, or related field.
• 0–2 years of professional experience; internships/projects welcome.
• Proficiency in Python and common data science libraries.
• Ability to read technical docs, investigate unfamiliar systems, and communicate conclusions.

Responsibilities

• Validate AI/ML models across use cases, focusing on generative AI and LLMs.
• Build reproducible testing frameworks and analyses to assess quality, safety, and reliability.
• Evaluate prompt behavior, retrieval quality, and guardrail effectiveness in AI systems.
• Apply ML methods to benchmark models, analyze errors, and compare options.

Skills

Python

ML engineering

Data analysis

Experiment design

Communication

Education

Master's degree / Bachelor's with relevant project experience

Tools

SQL

Git

Containers

Cloud platforms

Job description

Charles Schwab is seeking an early‑career engineer or quantitative researcher to join the AI Model Validation team in a hybrid role (4 days in-office, 1 day remote) in Texas. You will validate AI/ML models, build testing frameworks, and present evidence-based conclusions to technical teams.

You'll work on generative AI, LLMs, and model governance with collaboration across developers, data scientists, risk teams, and leadership.