Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
AI/ML Ops and Data Engineer
Reads like a ML Engineer role: putting models into production.
Southlake, TX; Austin, TX; Phoenix, AZ
Live, first seen by us 68 days ago- Pay
- Pay not listedSimilar roles state $166K–$240K
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign 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
From the employer’s posting
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
What you’ll bring
All qualificationsCore experience
- 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
Qualification wording
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
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Aug 28, 202668 days ago
- Recorded sightings
- 262
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 68
Similar jobs usually come down between day 6 and day 69.
From 4,347 similar postings that came down. Coming down is not always a hire.
Charles Schwab is hiring
18 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- BigQuery
- Docker
- GCP
- Google Cloud Storage
- Airflow
Where the posting names them
- 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
Your next step
Complete your application on www.schwabjobs.com. The employer’s form will show what is required.
Applying through Radancy (TalentBrew)
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Already applied? Track this application
About the role
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.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
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.
Job description
Your opportunity
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
- 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
Core 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’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:
- 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
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Southlake, TX; Austin, TX; Phoenix, AZ
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.
More source context
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:
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.