Reads like a ML Engineer role: putting models into production.
Southlake, Texas, United States; Austin, Texas, United States; Phoenix, Arizona, United States
Live, first seen by us 69 days agoDesign and build production-ready AI/ML security use cases on GCP
Lead end-to-end deployment from prototype to production with quality gates
Document and lead resolution of technical debt
Implement coding standards, test strategy, data quality checks, and alerting
Mentor MLOps and data engineers while staying hands-on in code
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
Mentor the MLOps and data engineers while remaining hands-on in code and delivery
Strong SQL and data modeling for analytics, scalability, and operational workloads
8+ years in data/software engineering, including 2+ years in technical leadership
Experience partnering with data scientists/MLE/Ops teams to deliver business outcomes
401(k) with company match and Employee stock purchase plan
Experience building and operating scalable batch/streaming pipelines
Experience leading design reviews, enforcing engineering standards, and mentoring data engineers
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Day 69
Similar jobs usually come down between day 6 and day 70.
Well past Charles Schwab’s usual: its jobs come down by about day 34.
From 4,481 similar postings that came down, and 98 of Charles Schwab’s. Coming down is not always a hire.
18 open jobs
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- 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
- 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)
Required Skills - 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)
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). 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. Required Skills
- 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
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New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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.
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).
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.
Required Skills
Required Work Experience
Core Responsibilities
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:
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Southlake, Texas, United States; Austin, Texas, United States; Phoenix, Arizona, United States
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. 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). 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.
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:
No clear work-authorization passage found. Eligibility is unconfirmed.