Q

Qualcomm

Designs mobile chips and licenses wireless patents

Staff Analytics Engineer (AI & Predictive) - AI & Predictive, Data Science

Full-TimeUpdated on 10/23/2026
$148.2k - $222.2k+ Annual discretionary bonus + Annual RSU grants
Senior
San Diego, CA, USA
In PersonFull-time onsite in San Diego, CA, five days per week.
AI & Machine LearningApplied Machine Learning
No H1B Sponsorship

About the job

Requirements
  • At least five years of hands-on experience in data science, applied machine learning, or machine learning engineering, with ownership of production systems.
  • Strong proficiency in Python for machine learning development, data processing, and application logic.
  • Deep experience with traditional machine learning techniques, including regression, classification, clustering, and time-series methods.
  • Proven experience building and deploying machine learning models in production environments.
  • Hands-on experience with Databricks, including application development using notebooks, workflows, dashboards, and machine learning pipelines.
  • Strong understanding of feature engineering, model evaluation, and explainability.
  • Experience collaborating with data engineering, business intelligence, and application teams.
Responsibilities
  • Design, develop, and deploy traditional machine learning models, including regression, classification, clustering, time-series forecasting, and anomaly detection.
  • Perform feature engineering, model selection, training, validation, and performance tuning on large-scale enterprise datasets.
  • Apply statistical and machine learning best practices to ensure model robustness, explainability, and business relevance.
  • Design and implement agentic artificial intelligence workflows in which autonomous or semi-autonomous agents orchestrate data access, machine learning inference, decision logic, and actions.
  • Build multi-step agent pipelines combining rules, machine learning models, and reasoning components to solve complex business problems.
  • Integrate agentic systems with enterprise data, machine learning models, and applications to enable intelligent automation and decision support.
  • Design and develop Databricks-native applications, including notebook-based apps, interactive dashboards, and parameterized data and machine learning workflows.
  • Build data and machine learning services and APIs using Databricks, Python, and Lakehouse capabilities.
  • Partner with analytics, business intelligence, and application teams to embed machine learning insights, predictions, and agent outputs into Databricks apps and business workflows.
  • Ensure Databricks apps meet performance, security, governance, and usability standards.
  • Operationalize machine learning models and agentic workflows in production pipelines, ensuring scalability, reliability, and monitoring.
  • Collaborate with data engineering teams to use curated Lakehouse data, feature stores, and governed datasets.
  • Implement model monitoring, drift detection, and retraining strategies to maintain long-term model effectiveness.
  • Develop end-to-end solutions spanning data ingestion, modeling, machine learning inference, agent execution, and user-facing applications.
  • Translate business and analytical requirements into scalable, maintainable machine-learning-powered data products.
  • Enable downstream consumption through Databricks apps, dashboards, APIs, and integrated enterprise applications.
  • Own production machine learning 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 machine learning, agentic artificial intelligence, and Databricks application patterns.
  • Influence architectural decisions, best practices, and technical standards across teams.
  • Mentor peers and improve machine learning rigor, engineering quality, and production readiness.
  • Independently deliver high-impact machine learning models, agentic AI workflows, and Databricks applications.
  • Bridge data science, machine learning engineering, and full-stack data application development.
  • Influence architecture, standards, and technical direction beyond assigned projects.
  • Act as a trusted technical partner to business, analytics, and engineering stakeholders.
  • Raise organizational maturity in traditional machine learning, agentic AI adoption, and production machine learning practices.
Desired Qualifications
  • Experience designing and implementing agentic artificial intelligence systems or autonomous decision-making workflows.
  • Familiarity with Lakehouse architectures, feature stores, and machine learning lifecycle management.
  • Experience with machine learning operations practices, continuous integration and continuous delivery, model monitoring, and retraining pipelines.
  • Exposure to cloud platforms such as AWS and scalable machine learning infrastructure.
  • Experience embedding machine learning and agent outputs into enterprise applications or analytics platforms.
  • Knowledge of data governance, access controls, and secure machine learning deployment.

About the company

Qualcomm designs the Snapdragon processors and modems inside many Android phones, and it licenses its wireless patents to device makers around the world. It helped commercialize CDMA, the cellular technology behind 3G networks, and its patents cover core parts of the 4G and 5G standards that phones use to connect. The company does not run its own chip factories; contract foundries make its chips, which it sells to makers of phones, PCs, cars, and connected devices. Device makers also pay Qualcomm royalties for using its patented technology, which forms a second business alongside chip sales. Qualcomm was founded in 1985 and is based in San Diego, California.

Company Size

10,001+

Company Stage

IPO

Headquarters

San Diego, California

Founded

1985

Get referred to Qualcomm

See people who can refer or advise you

Simplify Jobs

Simplify's Take

What believers are saying

  • Cars are a second engine: automotive chip revenue rose 61% to $1.59 billion in the June 2026 quarter.
  • Pays for learning: Qualcomm funds tuition assistance and apprenticeships and sells staff discounted shares through a stock purchase plan.
  • Profits support stability: Qualcomm earned $2.21 non-GAAP per share in the June 2026 quarter despite a 4% sales dip.

What critics are saying

  • Apple is walking away: Qualcomm expects Apple revenue to fall about 50% from the September to December 2026 quarter.
  • Data-center deals start thin: in July 2026, management said custom chips will cut chip gross margin 1.5 to 2 points.
  • Cuts keep trickling: Qualcomm filed WARN notices in April 2026 covering 144 layoffs, including 68 in San Diego.

What makes Qualcomm unique

  • Phones are only part of it: handsets were $5.09 billion of $8.50 billion chip revenue in fiscal Q3 2026.
  • Cloud giants buy its custom chips: two hyperscaler design wins start producing revenue in the December 2026 quarter.
  • It owns an AI software layer: Qualcomm completed its Modular acquisition in July 2026 for open generative AI software.

Help us improve and share your feedback! Did you find this helpful?

Benefits

  • Premium-free health coverage
  • Onsite health & fitness centers
  • Retirement programs
  • Disability & life insurance programs
  • Tuition reimbursement
  • Product discounts
  • Flexible time off
  • Parental leave

Growth & Insights and Company News

6 month growth

3%

1 year growth

1%

2 year growth

0%
Yahoo Finance
Oct 23rd, 2026
Qualcomm targets $15B data center sales by fiscal 2029 as handset revenue falls

Qualcomm is entering the data center chip market, with first revenue expected in the December quarter. The company says it has secured two custom chip customers, both global-scale hyperscalers, holds purchase orders from both, and has started making the wafers. Management targets data center revenue of $5 billion in fiscal 2027 and $15 billion in fiscal 2029. These are targets, not results. It closed its acquisition of Modular Inc. on July 29, 2026, to add data center software. The stock returned 4.5% over the past year, against 15.1% for the S&P 500. Revenue fell 4.0% in fiscal Q3 2026, and gross margin dropped to 53.1% from 55.6% a year earlier, as higher memory prices weighed.

CNBC
Oct 23rd, 2026
Indonesia's wealth fund steps in as stocks slide; Qualcomm plans layoffs, Lindt CEO exits

Indonesian stocks saw another round of panic selling this week after reports that index provider MSCI is considering downgrading the country's market status. Danantara, Indonesia's sovereign wealth fund, stepped in to stabilise the market. Its chief executive officer, Rosan Perkasa Roeslani, has called sharp pullbacks long-term buying opportunities. Qualcomm plans a new round of global layoffs, with figures undisclosed. Chief executive officer Cristiano Amon said in an internal memo that the cuts aim to build a stronger performance culture. Its shares have lagged the broader market this year. Lindt chief executive officer Adalbert Lechner stepped down on Monday after nearly 33 years at the company. His predecessor returns on an interim basis. Lindt raised prices about 16% in the first half to offset higher cocoa costs, then cut its full-year guidance twice as consumers pulled back.

Design & Reuse
Oct 22nd, 2026
Qualcomm buys RISC-V startup Akeana to push into AI and data-center chips.

Qualcomm buys RISC-V startup Akeana to push into AI and data-center chips. October 22, 2026 - By dealroom.co What's the deal? Qualcomm has acquired Akeana, a US semiconductor startup that designs processors using the open-source RISC-V architecture. Terms were undisclosed. The deal brings Akeana's technology and engineering team into Qualcomm to expand its push in AI and data centers. Who's Akeana? Founded in 2021 by engineers who previously built server processors at Marvell, the startup raised more than $100 million in August 2024 from investors including Kleiner Perkins, Mayfield, and Fidelity. Its RISC-V designs let companies customise processors for AI systems, computers, and data centers.

Arduino
Oct 21st, 2026
Discover the Qualcomm Academy new AI Associate Certification: Model to App at Maker Faire Rome!

Discover the Qualcomm Academy new AI Associate Certification: Model to App at Maker Faire Rome! Arduino Team - October 21st, 2026 Want real-world experience developing AI models and deploying applications using cutting-edge technologies such as the Arduino(R) UNO(TM) Q board? Qualcomm Academy has a new second-level program for you! The AI Associate Certification: Model to App is a hands-on, online, and self-paced program designed to provide experience with the end-to-end ML workflow, including data preparation, model creation, optimization, deployment, and on-device inference. Through approximately five to six hours of build-along training, you'll enjoy a combination of technical depth and practical application, helping you develop the confidence to create accurate, efficient, and production-ready AI solutions at the edge. Three projects. One complete edge AI journey. To achieve their certification, participants use a learning-focused development kit based on UNO Q to complete three real-world projects that span voice, vision, and sensor-based AI: * Wake Word Detection: Create and optimize a voice-enabled application that recognizes predefined wake words. * Person Recognition: Build a computer vision application that processes image data and performs real-time inference on an edge device. * Gesture Recognition: Train a model using IMU sensor data to detect and classify movements in real time. Each project connects model architecture, training, validation, quantization, deployment, and application integration so learners can explore the ML lifecycle in practice. Build skills for real-world edge AI development. By completing the certification, you will gain hands-on experience with developing ML models, preparing data, quantizing and optimizing models to explore tradeoffs among accuracy, latency, power consumption, and performance, and visualizing model graphs. You will also gain experience with AI development toolchains, explore MCU and MPU capabilities, develop real-time applications, and work with FastRPC communication for AI workloads. The program is designed for developers and engineers, embedded systems professionals, IoT and robotics developers, students, and industry professionals interested in gaining practical experience with ML and edge AI. Learners should have basic Python skills, familiarity with an IDE, introductory knowledge of PyTorch and ML concepts, and prior hands-on experience equivalent to the Qualcomm Academy foundational AI certificate programs. Flexible learning, practical results. The AI Associate Certification: Model to App is available online and can be completed at each learner's own pace. You may purchase the program via Qualcomm Academy. After successfully completing the certification requirements, you will receive a Qualcomm Technologies certificate and badge that can be displayed on your CV and LinkedIn profile. Start building - from model to app! Take the next step in your AI development journey. Enroll in the AI Associate Certification: Model to App and gain hands-on experience applying ML concepts to applications running at the edge. Visiting Maker Faire Rome (October 23rd-25th)? Make sure to stop by the Arduino booth to talk to the team about how you can get your AI Associate Certification: Model to App. Qualcomm Academy is a program of Qualcomm Technologies, Inc. and/or its subsidiaries. Arduino and UNO are trademarks or registered trademarks of Arduino S.r.l.

CNBC
Oct 21st, 2026
Tokenized stock trading surges overseas to $11.31B on Robinhood Chain as Goldman, Microsoft object in US

Tokenized stock trading is growing overseas while major US companies resist it at home, according to Bitwise Asset Management's latest quarterly report. On Robinhood Chain, tokenized stock volume rose from $526 million in July to $2.21 billion in August, then to $11.31 billion in September. Tokenized equities were also the fastest-growing category on Solana. Goldman Sachs, Microsoft, Qualcomm, Caterpillar, McDonald's, Western Digital, and Alphabet have objected to tokenized versions of their shares trading on OKXICE, a venue launched by crypto exchange OKX and Intercontinental Exchange. Sixteen companies have now objected. The US Securities and Exchange Commission's innovation exemption lets companies opt out. OKXICE co-chairman Andrew Cuomo said many companies would "wait and see" before taking part.