Modem Machine Learning Engineer
Core
Apply advanced machine learning techniques to next-generation modem systems, focusing on data engineering, model development, deployment, and lifecycle management for production-ready ML solutions.
Role type
Senior IC machine learning engineer (modem systems)
Builds
Production ML models, MLOps frameworks, and data platforms for modem and wireless systems
Domain
Telecommunications / Wireless / Hardware-Software Integration
Deliverable
production ML models
Required skills
Python, C/C++, deep learning architectures (CNNs, RNNs, LSTMs, Transformers), MLOps, time-series forecasting, sequence modeling, model optimization for edge devices, data drift detection, ETL pipelines
Preferred skills
PyTorch, TensorFlow, Keras, AWS (S3, Glue, EMR), Docker, Kubernetes, Kafka, RabbitMQ, Spark, Databricks, Delta Lake, quantization tools, cloud ML platforms (SageMaker)
Technologies
PyTorch, TensorFlow, Keras, AWS, Docker, Kubernetes, Kafka, RabbitMQ, Spark, Databricks, Prometheus, Grafana, Datadog, Splunk
Responsibilities
Identify and prioritize high-impact ML use cases within modem systems; Design, develop, and train robust ML/DL models for modem applications; Build and integrate automated, end-to-end ML pipelines; Design and maintain state-of-the-art MLOps infrastructure; Deploy and optimize ML models for on-device and modem targets; Implement robust model performance monitoring and drift detection; Collaborate across systems, test, and platform teams for production rollout.
Seniority
Mid-Senior, hands-on IC