Staff Analytics Engineer (AI & Predictive)
Technology, Data & Digital · Data, AI & Analytics · Data Science · Machine Learning · DevOps
In short
Staff Analytics Engineer (AI & Predictive) at Qualcomm is responsible for designing, building, and operationalizing predictive analytics, traditional machine learning models, agentic AI systems, and Databricks-native data applications. This senior role requires expertise in data science, ML engineering, and full-stack data application development, with a focus on production-grade solutions.
Responsibilities
- Design, develop, and deploy traditional machine learning models (regression, classification, clustering, time-series forecasting, anomaly detection).
- Perform feature engineering, model selection, training, validation, and performance tuning on large-scale enterprise datasets.
- Apply statistical and ML best practices for model robustness, explainability, and business relevance.
- Design and implement agentic AI workflows where autonomous or semi-autonomous agents orchestrate data access, ML inference, decision logic, and actions.
- Build multi-step agent pipelines combining rules, ML models, and reasoning components.
- Integrate agentic systems with enterprise data, ML models, and applications.
- Design and develop Databricks-native applications (notebook-based apps, interactive dashboards, parameterized data/ML workflows).
- Build data and ML services/APIs leveraging Databricks, Python, and Lakehouse capabilities.
- Embed ML insights, predictions, and agent outputs into Databricks apps and business workflows.
- Ensure Databricks apps meet performance, security, governance, and usability standards.
- Operationalize ML models and agentic workflows into production pipelines, ensuring scalability, reliability, and monitoring.
- Collaborate with data engineering teams to leverage curated Lakehouse data, feature stores, and governed datasets.
- Implement model monitoring, drift detection, and retraining strategies.
- Develop end-to-end solutions spanning data ingestion, modeling, ML inference, agent execution, and user-facing applications.
- Translate business and analytical requirements into scalable, maintainable ML-powered data products.
- Own production ML models, agentic systems, and Databricks applications, including monitoring, troubleshooting, and root-cause analysis.
- Implement logging, alerting, and observability for models, agents, and applications.
- Drive continuous improvements in model accuracy, system reliability, and user experience.
- Serve as a technical 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 on ML rigor, engineering quality, and production readiness.
Requirements
- 5+ years of hands-on experience in data science, applied machine learning, or ML engineering, with ownership of production systems.
- Strong proficiency in Python 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 deploying ML models in production environments.
- Hands-on experience with Databricks, including Databricks application development (notebooks, workflows, dashboards, ML pipelines).
- Strong understanding of feature engineering, model evaluation, and explainability.
- Experience collaborating with data engineering, BI, and application teams.
Desired Qualifications
- Experience designing and implementing agentic AI systems or autonomous decision-making workflows.
- Familiarity with Lakehouse architectures, feature stores, and ML lifecycle management.
- Experience with MLOps 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 into enterprise applications or analytics platforms.
- Knowledge of data governance, access controls, and secure ML deployment.
Benefits
- Competitive annual discretionary bonus program.
- Opportunity for annual RSU grants.
- Highly competitive benefits package designed to support your success at work, at home, and at play.
- Access to US benefits details via a provided link.
#AI#Predictive Analytics#Machine Learning#Agentic AI#Databricks#Data Science#ML Engineering#Full-Stack#Data Applications
Company
Qualcomm
Job Posted
1 week ago
Employment Type
Full Time
WorkMode
On Site
Experience Level
Senior
Locations
San Diego, United States of America
Applicants
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