Machine Learning Ops Data Engineer

Charles Schwab Inc.
Southlake, United States of America
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate
Compensation
$ 185K

Job location

Southlake, United States of America

Tech stack

Artificial Intelligence
Airflow
Automation of Tests
Google BigQuery
Cloud Computing Security
Continuous Integration
Data Validation
Data Flow Control
Identity and Access Management
Python
Machine Learning
Role-Based Access Control
Reliability Engineering
Standard Sql
Runbook
Software Engineering
Strategies of Testing
Data Logging
Google Cloud Platform
Cloud Monitoring
System Availability
Delivery Pipeline
Build Management
Containerization
Git Flow
Google Cloud Functions
Machine Learning Operations
Software Coding
Software Version Control
Docker

Job description

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., * 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

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)

What you have

Required Work Experience

  • 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

Benefits & conditions

Pulled from the full job description

  • Tuition reimbursement
  • Paid parental leave
  • Employee stock purchase plan
  • Parental leave
  • 401(k)
  • Health insurance
  • 401(k) matching, 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

About the company

At 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., 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.

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