The Modem Machine Learning Engineer at Qualcomm Technologies, Inc. focuses on applying advanced machine learning techniques to next-generation modem systems. This role involves collaboration with modem, systems, and software teams to deliver production-ready ML solutions. The engineer will emphasize modern deep learning architectures and build scalable MLOps frameworks while ensuring continuous model health monitoring. The position requires a strong foundation in machine learning algorithms and hands-on programming experience.

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field.
• At least 1 year of relevant experience or a Master's degree.
• Strong hands-on programming experience in Python and/or C/C++.
• Solid foundations in machine learning algorithms, probability, statistics, and software engineering principles.

• Identify, scope, and prioritize high-impact machine learning use cases within modem and wireless systems.
• Design, develop, and train robust ML/DL models tailored for modem applications.
• Build and integrate automated, end-to-end ML pipelines encompassing data ingestion, feature generation, model training, evaluation, and deployment.
• Design and maintain state-of-the-art MLOps infrastructure to enable reproducible experimentation and strict model versioning.
• Deploy and optimize ML models for on-device and modem targets with strict latency, memory, and compute constraints.
• Implement robust model performance monitoring, establishing KPI regression tracking and automated detection for data and concept drift.
• Collaborate closely across systems, test, and platform teams to ensure a seamless production rollout.
• Design and implement ETL, data platform, MLOps, CI/CD, observability, and governance pipelines across on-premises and cloud environments.

• Qualcomm offers competitive compensation, annual bonuses, stock programs, comprehensive healthcare coverage, retirement plans, wellness programs, parental leave, flexible work options, and professional development opportunities.