Careers
Quick summary
- Work type
- On-site
- Location
- —
- Posted
- 22 days ago
Market check
Salary context
How this pay compares to similar roles
This listing doesn't post a salary. Most similar roles pay $152,037–$208,800.
Based on 238 similar postings.
Employer
About Qualcomm
Qualcomm is a leading American semiconductor and telecommunications company based in San Diego, CA.
Qualcomm currently has 558 open roles on FindRole.
Listed pay typically runs $154,000–$231,000 across 401 roles with salary data.
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At a glance
TL;DR · Careers
The Modem Machine Learning Engineer role at the cutting edge of modem systems involves applying advanced machine learning techniques to develop production-ready solutions. This senior position requires close collaboration with various engineering teams to build robust ML/DL models tailored for modem applications, focusing on time-series forecasting and sequence modeling. Day-to-day responsibilities include designing scalable MLOps frameworks, automating end-to-end ML pipelines, deploying optimized models in constrained environments, and implementing continuous performance monitoring. Key technologies encompass Python/C++, deep learning architectures like CNNs and RNNs, and frameworks such as PyTorch and TensorFlow. The role also demands expertise in AWS services, Docker/Kubernetes, and observability tools for managing large-scale datasets and ensuring model health in dynamic production settings.
Skills
What you'll do
- Identify and prioritize high-impact machine learning use cases for modem systems.
- Develop robust ML/DL models using advanced deep learning architectures for modem applications.
- Build automated end-to-end ML pipelines for data ingestion, training, evaluation, and deployment.
- Design MLOps infrastructure to enable reproducible experimentation and strict model versioning.
- Optimize ML models for on-device deployments with hardware and firmware constraints.
- Implement continuous monitoring of model performance and detect drift in production environments.
- Build and manage ML data platforms using AWS services and containerization technologies.
What we're looking for
- Strong hands-on experience in Python or C/C++ programming.
- Solid understanding of machine learning algorithms, probability, statistics, and software engineering principles.
- Experience with deep learning architectures like CNNs, RNNs, LSTMs, and Transformers.
- Proficiency in ML frameworks such as PyTorch, TensorFlow, and Keras.
- Expertise in building production-grade ML pipelines for large datasets.
- Deep experience with MLOps systems including experiment tracking and model lifecycle management.
- Strong software engineering skills for debugging complex integrated systems.
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