Modem Machine Learning Engineer

Company

Qualcomm Technologies, Inc.

Job Area

Engineering Group, Engineering Group > Modem Technologies Software

General Summary

The Modem Machine Learning Engineer applies advanced machine learning techniques to next‑generation modem systems, working across data engineering, model development, deployment, and lifecycle management. This role partners closely with modem, systems, and software teams to deliver production‑ready ML solutions. You will place a strong emphasis on modern deep learning architectures, building scalable MLOps frameworks, and ensuring continuous model health monitoring in dynamic production environments.

Key Responsibilities

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, leveraging time‑series forecasting, sequence modeling, and modern deep learning architectures.

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, strict model versioning, automation, and the scalable onboarding of new ML use cases.

Deploy and heavily optimize ML models for on‑device and modem targets, specifically focusing on HW and firmware integrated environments with strict latency, memory, and compute constraints.

Implement robust model performance monitoring, establishing KPI regression tracking and automated detection for data and concept drift across both cloud and on‑target deployments.

Collaborate closely across systems, test, and platform teams to ensure a seamless production rollout and sustained model performance over time.

Design and implement ETL, data platform, MLOps, CI/CD, observability, and governance pipelines across on-premises and cloud environments.

Build and manage ML data platforms utilizing hands-on experience with AWS (S3, Glue, EMR), containers (Docker, Kubernetes), streaming/messaging (Kafka, RabbitMQ), data platforms (Spark, Databricks, Delta Lake/Iceberg/Hudi, SQL, Postgres), and observability stacks (Prometheus/Grafana, Datadog, Splunk).

Minimum Qualifications

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 2+ years of Software Engineering, Electrical Engineering, or related work experience.

OR

Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 1+ year of Software Engineering, Electrical Engineering, or related work experience.

OR

PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field.

Minimum Qualifications

• Bachelor’s degree with at least 1 year of relevant experience or 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.