Modem Machine Learning Engineer

Qualcomm • San Diego, CA

5d • $135,400 - $203,200

About The Position

The Modem Machine Learning Engineer applies advanced machine learning techniques to next-generation modem systems, spanning data engineering, model development, deployment, and lifecycle management. The role partners with modem, systems, and software teams to deliver production-ready ML solutions, with emphasis on modern deep learning architectures, scalable MLOps frameworks, and continuous model health monitoring in dynamic production environments.

The engineer develops ML solutions for modem and wireless applications, builds automated data and model pipelines, optimizes models for on-device and modem targets with strict latency, memory, and compute constraints, and maintains production monitoring and data platforms across on-premises and cloud environments.

Requirements

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or a related field and 2+ years of Software Engineering, Electrical Engineering, or related work experience; OR a master's degree in one of these fields and 1+ year of related work experience; OR a PhD in one of these fields.
• Bachelor’s degree with 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.

Nice To Haves

• Hands-on experience with deep learning architectures including CNNs, RNNs, GRUs, LSTMs, Transformers, and related sequence models.
• Proficiency with ML frameworks such as PyTorch, TensorFlow, or Keras.
• Experience building production-grade ML pipelines for large-scale structured and unstructured datasets.
• Experience with MLOps systems, including experiment tracking, model lifecycle management, CI/CD for ML, and cloud/on-device co-development environments.
• Experience implementing data drift, concept drift, and model performance monitoring using defined KPIs in production.
• Strong software engineering skills, including object-oriented design, debugging complex integrated systems, and working within real-time execution constraints.
• Exposure to on-device ML deployment, quantization, and neural network optimization tools.
• Familiarity with cloud ML platforms such as AWS SageMaker, containerization with Docker or Kubernetes, and automation/orchestration tools.
• Hands-on experience with AWS S3, Glue, and EMR; Docker and Kubernetes; Kafka or RabbitMQ; Spark, Databricks, Delta Lake, Iceberg, Hudi, SQL, or Postgres; and Prometheus/Grafana, Datadog, or Splunk.

Responsibilities

• Identify, scope, and prioritize high-impact machine learning use cases within modem and wireless systems.
• Design, develop, and train robust ML/DL models for modem applications, using time-series forecasting, sequence modeling, and modern deep learning architectures.
• Build and integrate end-to-end ML pipelines for data ingestion, feature generation, model training, evaluation, and deployment.
• Design and maintain MLOps infrastructure supporting reproducible experimentation, model versioning, automation, and scalable onboarding of ML use cases.
• Deploy and optimize ML models for on-device and modem targets, including hardware- and firmware-integrated environments with strict latency, memory, and compute constraints.
• Implement model performance monitoring, KPI regression tracking, and automated data- and concept-drift detection across cloud and on-target deployments.
• Collaborate with systems, test, and platform teams to support production rollout and sustained model performance.
• 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 using relevant cloud, container, streaming, data-platform, database, and observability technologies.

Benefits

• Competitive annual discretionary bonus program.
• Opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for the annual bonus).
• Competitive benefits package designed to support employees at work, at home, and at play.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level