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.
Reads like a ML Engineer role: putting models into production.
Frisco, TX, United States
Live, first seen by us 88 days agoEmployment type in the employer’s posting: Full-timeFrom the employer’s posting
**Sponsorship for Work Authorization is not available for this posting
Build and maintain batch and streaming data pipelines using BigQuery, dbt, Airflow and Pub/Sub
Design layered data models and semantic layers that scale with business needs
Optimize BigQuery performance and cost through partitioning and clustering
Convert prototype notebooks and models into versioned, testable Python packages
Deploy and manage training and inference workflows on GCP with Cloud Run, GKE and Vertex AI
Architect, build, and maintain batch and streaming data pipelines using BigQuery, dbt, Airflow/Cloud Composer, and Pub/Sub
Design and implement layered data models, semantic layers, and modular pipelines that scale as business needs evolve
Optimize BigQuery for performance and cost efficiency, including partitioning, clustering, and workload-aware modeling
Convert prototype notebooks and models into production-grade, versioned, testable Python packages
Deploy and manage training and inference workflows on GCP using Cloud Run, GKE, and Vertex AI
3+ years of hands-on experience building data pipelines in a code-first environment using Python, SQL, and dbt
1+ year of experience with real-time or event-driven systems such as Pub/Sub, Dataflow, or comparable streaming frameworks
2+ years of experience owning technical decisions or helping lead engineering direction
1+ year of hands-on experience with graph databases, including graph data modeling, relationship-centric querying, or graph-based problem solving
Experience with GCP and/or AWS
Experience with ML platform tooling or monitoring such as MLflow, Evidently, or Vertex AI
Knowledge of semantic search, vector embeddings, LLM orchestration, or RAG workflows
Experience with graph database technologies such as Neo4j, Neptune, or similar platforms
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$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.
Day 88
Up longer than most. Similar jobs usually come down between day 6 and day 69.
From 4,296 similar postings that came down. Coming down is not always a hire.
6 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- Familiarity with geospatial data or map-based modeling - Some JavaScript experience for lightweight UI or prototyping work Why This Role Will Excite You
ML/AI Platform Engineering — 20% - Convert prototype notebooks and models into production-grade, versioned, testable Python packages - Deploy and manage training and inference workflows on GCP using Cloud Run, GKE, and Vertex AI
- MS in Computer Science with 4+ years of experience, or BS in Computer Science with 6+ years of experience - 3+ years of hands-on experience building data pipelines in a code-first environment using Python, SQL, and dbt - 1+ year of experience with real-time or event-driven systems such as Pub/Sub, Dataflow, or comparable streaming frameworks
Preferred Experience - Experience with GCP and/or AWS - Experience with ML platform tooling or monitoring such as MLflow, Evidently, or Vertex AI
Data Engineering & Pipeline Development (Primary) — 60% - Architect, build, and maintain batch and streaming data pipelines using BigQuery, dbt, Airflow/Cloud Composer, and Pub/Sub - Design and implement layered data models, semantic layers, and modular pipelines that scale as business needs evolve
- Establish and enforce best practices for data quality, observability, lineage, and schema governance - Optimize BigQuery for performance and cost efficiency, including partitioning, clustering, and workload-aware modeling - Work with both structured data and unstructured data such as web logs, call center transcripts, images, and video when required by the use case
- Convert prototype notebooks and models into production-grade, versioned, testable Python packages - Deploy and manage training and inference workflows on GCP using Cloud Run, GKE, and Vertex AI - Implement CI/CD, model versioning, rollback strategies, and operational guardrails for ML systems
- Experience with GCP and/or AWS - Experience with ML platform tooling or monitoring such as MLflow, Evidently, or Vertex AI - Knowledge of semantic search, vector embeddings, LLM orchestration, or RAG workflows
- Knowledge of semantic search, vector embeddings, LLM orchestration, or RAG workflows - Experience with graph database technologies such as Neo4j, Neptune, or similar platforms - Familiarity with use cases involving knowledge graphs, entity relationships, recommendation systems, fraud patterns, or connected data analysis
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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.
What You’ll Do
Data Engineering & Pipeline Development (Primary) — 60%
ML/AI Platform Engineering — 20%
Applied AI & Real-Time Decisioning — 20%
Cross-Functional Collaboration
What We’re Looking For
We are looking for someone who is not only technically strong, but also:
Qualifications
Preferred Experience
Why This Role Will Excite You
Workplace
Public Storage is an equal opportunity employer and embraces diversity. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other protected status. All qualified candidates are encouraged to apply.
**Sponsorship for Work Authorization is not available for this posting. Candidates must be authorized to work in the U.S. without restrictions or requiring sponsorship now or in the future. We do not provide training plans or support for F-1 OPT, STEM OPT extensions, or future visa sponsorship.**
Since opening our first self-storage facility in 1972, Public Storage has grown to become the largest owner and operator of self-storage facilities in the world. With thousands of locations across the U.S. and Europe, and more than 170 million net rentable square feet of real estate, we're also one of the largest landlords.
We've been recognized as A Great Place to Work by the Great Place to Work Institute. And, our employees have also voted us as having Best Career Growth, ranked us in the Top 5% for Work Culture, and in the Top 10% for Diversity and Inclusion.
We're a member of the S&P 500 and FT Global 500. Our common and preferred stocks trade on the New York Stock Exchange.
Public Storage is the nation’s leading self-storage provider, recognized for its iconic orange doors and commitment to delivering simple, reliable solutions to millions of customers across the country. We are expanding our creative team to enhance our consistent and engaging visual brand presence.
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Frisco, TX, United States
Workplace - One of our values pillars is to work as One Team and we believe that there is no replacement for in-person collaboration but understand the value of some flexibility. Public Storage teammates are expected to work in the office five days each week with the option to take up to three flexible remote days per month. Public Storage is an equal opportunity employer and embraces diversity. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other protected status. All qualified candidates are encouraged to apply.
Public Storage is an equal opportunity employer and embraces diversity. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other protected status. All qualified candidates are encouraged to apply. **Sponsorship for Work Authorization is not available for this posting. Candidates must be authorized to work in the U.S. without restrictions or requiring sponsorship now or in the future. We do not provide training plans or support for F-1 OPT, STEM OPT extensions, or future visa sponsorship.** Company Description