Staff Analytics Engineer (AI & Predictive)

Qualcomm

Quick summary

Work type
On-site
Location
San Diego, CA
Salary
$142,100–$213,100 / yr
Posted
47 days ago
Closes
Oct 17, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $209k
This role $178k
$130k most similar roles pay here $259k

This role pays less than 73% of similar roles. Most pay $172,375–$246,150 — the shaded band above. At the midpoint, this role pays about $178k versus about $209k for comparable roles.

Based on 240 similar postings.

Employer

About Qualcomm

Qualcomm is a leading American semiconductor and telecommunications company based in San Diego, CA.

Qualcomm currently has 558 open roles on FindRole.

Listed pay typically runs $154,000–$231,000 across 401 roles with salary data.

Most-posted roles

View all roles at Qualcomm

At a glance

TL;DR · Staff Analytics Engineer (AI & Predictive)

The Staff Analytics Engineer (AI & Predictive) is a senior role within Qualcomm’s Information Technology Group, focusing on designing and operationalizing predictive analytics, machine learning models, and agentic AI systems using Databricks technology to drive business outcomes. This hands-on position involves developing traditional ML models, feature engineering, model validation, and deploying production-grade solutions that integrate with enterprise data and applications. Responsibilities include building multi-step agent pipelines for intelligent automation, creating Databricks-native applications, and ensuring performance standards are met while collaborating closely with analytics and BI teams. The role requires expertise in Python, classical ML techniques, and Databricks application development, along with experience in productionizing models and implementing monitoring strategies to maintain long-term effectiveness.

What you'll do

  • Design, develop, and deploy traditional machine learning models for enterprise datasets.
  • Implement agentic AI workflows combining rules, ML models, and reasoning components.
  • Develop Databricks-native applications including notebooks, dashboards, and data/ML workflows.
  • Operationalize ML models into production pipelines ensuring scalability and reliability.
  • Translate business requirements into scalable ML-powered data products end-to-end.
  • Own and monitor production ML models, agentic systems, and Databricks applications.

What we're looking for

  • 5+ years of hands-on experience in data science or ML engineering with production system ownership.
  • Strong proficiency in Python for ML development, data processing, and application logic.
  • Deep expertise in traditional ML techniques including regression, classification, clustering, and time series forecasting.
  • Proven track record of building and deploying ML models in production environments.
  • Hands-on experience with Databricks for application development, including notebooks, workflows, and dashboards.
  • Experience collaborating with data engineering, BI, and application teams on ML projects.

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