Staff Analytics Engineer (AI & Predictive)
Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Mar 4, 2026. Qualcomm scores B on the Alion truth index.
Company:
Qualcomm IncorporatedJob Area:
Information Technology Group, Information Technology Group > Data ScienceGeneral Summary:
TheStaff Analytics Engineer (AI & Predictive) is a senior, hands-on individual contributor responsible for designing, building, and operationalizingpredictive analytics, traditional machine learning models, agentic AI systems, and Databricks-native data applications that drive real business outcomes. This role operates at the intersection ofdata science, ML engineering, and full-stack data application development, with a strong focus onproduction-grade solutions.
This position requires deep expertise inclassical ML techniques, agent-based AI workflows, and Databricks application development, along with strong ownership of end-to-end delivery-from data preparation and modeling to deployment, monitoring, and user-facing experiences.
This role requires full-time onsite work in San Diego, CA (5 days per week).
**This position is not eligible for Qualcomm immigration sponsorship.**
Key Responsibilities
Traditional Machine Learning & Analytics
Design, develop, and deploytraditional machine learning models, including regression, classification, clustering, time-series forecasting, and anomaly detection.
Performfeature engineering, model selection, training, validation, and performance tuning on large-scale enterprise datasets.
Apply soundstatistical and ML best practices to ensure model robustness, explainability, and business relevance.
Agentic AI & Intelligent Automation
Design and implementagentic AI workflows, where autonomous or semi-autonomous agents orchestrate data access, ML inference, decision logic, and actions.
Buildmulti-step agent pipelines that combine rules, ML models, and reasoning components to solve complex business problems.
Integrate agentic systems withenterprise data, ML models, and applications to enable intelligent automation and decision support.
Databricks Application Development
Design and developDatabricks-native applications, includingnotebook-based apps, interactive dashboards, and parameterized data/ML workflows.
Builddata and ML services/APIs leveraging Databricks, Python, and Lakehouse capabilities.
Partner with analytics, BI, and application teams to embedML insights, predictions, and agent outputs directly into Databricks apps and business workflows.
Ensure Databricks apps meetperformance, security, governance, and usability standards.
ML Engineering & Productionization
Operationalize ML models and agentic workflows intoproduction pipelines, ensuring scalability, reliability, and monitoring.
Collaborate with data engineering teams to leveragecurated Lakehouse data, feature stores, and governed datasets.
Implementmodel monitoring, drift detection, and retraining strategies to maintain long-term model effectiveness.
Full-Stack Data Enablement
Develop end-to-end solutions that spandata ingestion, modeling, ML inference, agent execution, and user-facing applications.
Translate business and analytical requirements intoscalable, maintainable ML-powered data products.
Enable downstream consumption throughDatabricks apps, dashboards, APIs, and integrated enterprise applications.
Production Support & Operational Excellence
Ownproduction ML models, agentic systems, and Databricks applications, including monitoring, troubleshooting, and root-cause analysis.
Implement logging, alerting, and observability formodels, agents, and applications.
Drive continuous improvements inmodel accuracy, system reliability, and user experience.
Technical Leadership & Influence
Serve as atechnical authority in traditional ML, agentic AI, and Databricks application patterns.
Influence architectural decisions, best practices, and technical standards across teams.
Mentor peers and raise the bar onML rigor, engineering quality, and production readiness.
Qualifications
Required Skills & Experience
5+ years of hands-on experience indata science, applied machine learning, or ML engineering, with ownership of production systems.
Strong proficiency inPython for ML development, data processing, and application logic.
Deep experience with traditional ML techniques (e.g., regression, classification, clustering, time series).
Proven experience building and deployingML models in production environments.
Hands-on experience withDatabricks, including Databricks application development (notebooks, workflows, dashboards, ML pipelines).
Strong understanding offeature engineering, model evaluation, and explainability.
Experience collaborating withdata engineering, BI, and application teams.
Preferred / Nice-to-Have Qualifications
Experience designing and implementingagentic AI systems or autonomous decision-making workflows.
Familiarity withLakehouse architectures, feature stores, and ML lifecycle management.
Experience withML Ops practices, CI/CD, model monitoring, and retraining pipelines.
Exposure to cloud platforms (e.g., AWS) and scalable ML infrastructure.
Experience embedding ML and agent outputs intoenterprise applications or analytics platforms.
Knowledge ofdata governance, access controls, and secure ML deployment.
What Defines Success at the Staff Level
Independently delivershigh-impact ML models, agentic AI workflows, and Databricks applications.
Bridgesdata science, ML engineering, and full-stack data app development.
Influences architecture, standards, and technical direction beyond assigned projects.
Acts as a trusted technical partner tobusiness, analytics, and engineering stakeholders.
Raises organizational maturity intraditional ML, agentic AI adoption, and production ML practices.
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Pay range and Other Compensation & Benefits :
$148,200.00 - $222,200.00The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer - and you can review more details about our US benefits at this link.
If you would like more information about this role, please contact Qualcomm Careers.