AI/ML Ops and Data Engineer

Charles Schwab Inc. • Southlake, TX

20h • Onsite

About The Position

Hands-on technical lead responsible for taking AI/ML projects from development to production in Google Cloud Platform (GCP). This role owns architecture, implementation, deployment, and operations. 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).

Requirements

• Expert-level Google Cloud experience, especially services used for AI/ML use cases (e.g., BigQuery, Vertex AI, GCS, Dataflow, Pub/Sub, Cloud Run/GKE, Composer/Airflow, IAM, Cloud Monitoring/Logging)
• Expert Python for production-grade data and backend engineering
• Strong SQL and data modeling for analytics, scalability, and operational workloads
• Strong CI/CD and containerization skills (Docker, Git workflows, automated testing, release pipelines)
• Solid cloud security and governance practices (IAM, secrets, least privilege, auditability)
• Strong observability and reliability engineering skills (monitoring, alerting, incident response, SLAs/SLOs)
• Fundamental understanding of AI/ML lifecycle/model development needed to productionize AI/ML systems (training/serving integration, model versioning, pipeline monitoring support)
• 8+ years in data/software engineering, including 2+ years in technical leadership
• Proven track record delivering production grade AI/ML use cases on GCP or other cloud providers
• Experience building and operating scalable batch/streaming pipelines
• Experience leading design reviews, enforcing engineering standards, and mentoring data engineers
• Demonstrated support of critical systems in production
• Experience partnering with data scientists/MLE/Ops teams to deliver business outcomes

Responsibilities

• Design and build production-ready AI/ML powered, security related use cases on GCP
• Lead end-to-end deployment from prototype to production with clear quality gates
• Understand, document, and lead the resolution of technical debts
• Implement coding standards, test strategy, data quality checks, alerting mechanisms, and operational runbooks
• Ensure platform reliability, security, and cost efficiency
• Mentor the MLOps and data engineers while remaining hands-on in code and delivery

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed