Senior AIML Data Engineer

What Youll Do

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
• Leverage BQML and related data science capabilities for use cases such as anomaly detection classification and operational decision support
• Deliver reliable scalable and high-performing pipelines that enable downstream ML analytics and operational applications

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
• Implement CI/CD model versioning rollback strategies and operational guardrails for ML systems
• Evaluate emerging GCP and third-party products; build shared libraries templates and internal tooling that accelerate delivery across teams
• Enable ML teams to ship faster with fewer operational failure points

Applied AI & Real-Time Decisioning 20%

• Support real-time event-driven inference and streaming feature delivery for mission-critical decisions including recommendation systems dynamic experimentation and agentic AI use cases
• Contribute to internal LLM-based assistants retrieval-augmented generation (RAG) systems and automation agents
• Implement model monitoring drift detection alerting and performance tracking frameworks
• Evaluate and apply graph-based data patterns where they improve recommendations relationship analysis knowledge retrieval or decision intelligence

Cross-Functional Collaboration

• Partner with data scientists analysts and engineers to operationalize models semantic layers and data products into maintainable production systems
• Collaborate with pricing digital product analytics and business teams to stage rollouts support experiments and define success metrics
• Participate in architecture reviews mentor engineers and communicate technical trade-offs clearly
• Contribute to an engineering culture grounded in ownership curiosity thoughtful debate and continuous learning

What Were Looking For

We are looking for someone who is not only technically strong but also:

• Passionate about building high-quality systems
• Hardworking and dependable with strong ownership of outcomes
• Eager to learn experiment and deepen expertise over time
• Comfortable in a fast-paced environment where priorities can shift quickly
• Open to collaboration feedback and healthy technical debate
• Interested in growing both technical depth and leadership capability over the long term

Qualifications :

Qualifications

• 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
• 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

Preferred Experience

• 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
• Familiarity with use cases involving knowledge graphs entity relationships recommendation systems fraud patterns or connected data analysis
• Domain experience in pricing recommendations forecasting or large-scale customer analytics
• Familiarity with geospatial data or map-based modeling
• Some JavaScript experience for lightweight UI or prototyping work

Why This Role Will Excite You

• Youll work in a fast-moving environment where decisions are made quickly and your work drives real business outcomes
• Youll own meaningful parts of the platform not just execute isolated tasks
• Youll build end-to-end solutionsfrom ingestion and transformation to ML inference and production integration
• Youll have the opportunity to learn quickly expand your scope and grow your technical leadership
• Youll join a team that values curiosity execution and continuous improvement

Additional Information :

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.

**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.**

Remote Work :

No

Employment Type :

Full-time