Machine Learning Engineer (Irvine)

Machine Learning Engineer

Skyworks Solutions is seeking a Machine Learning Engineer (MLE) to join our rapidly growing AI / ML team in Irvine, CA. This is a highly technical, hands-on role designed for individuals who thrive at the intersection of cutting-edge machine learning, signal processing, and semiconductor innovation. If you're looking to apply your ML expertise to high-impact, real-world engineering challenges in the analog and RF domain, this is your opportunity.

Skyworks is an innovator of high-performance analog semiconductors enabling next-generation wireless communications. From 5G to IoT to automotive, our technologies are helping to connect the world. At Skyworks, you'll find a fast-paced environment with a flat organizational structure and global collaboration. We value open communication, creativity, mutual respect, and technical excellence.

As a Machine Learning Engineer on the Data Analytics and AI Enablement team, you will lead and contribute to projects that apply advanced ML and deep learning to a variety of use cases across the companyincluding design automation, yield prediction, anomaly detection, signal classification, and device modeling. You will collaborate with world-class engineers across electrical, RF, product, and manufacturing domains to deliver real business impact through data and AI.

Predictive analytics for yield and quality improvement

Optimization of circuit or device parameters

RF signal modeling and anomaly detection

Root-cause analysis across test and manufacturing data

Own the end-to-end ML pipeline : data acquisition, feature engineering, model selection, training, evaluation, deployment, and monitoring.

Collaborate with cross-functional stakeholders including design engineers, process experts, and product owners to understand problem statements and translate them into ML solutions.

Work on both research-oriented prototypes and production-grade deployments.

Stay up-to-date with current trends in ML, especially those relevant to semiconductor, signal processing, or high-dimensional time-series data.

BS and 8 years experience (Ph.D. preferred) in Machine Learning, Computer Science, Electrical Engineering, Applied Mathematics, or a related field.

Strong theoretical and practical experience in machine learning and deep learning, including CNNs, transformers, time-series models, or probabilistic methods.

Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, Scikit-learn.

Solid understanding of statistics, optimization, and model evaluation techniques.

Excellent communication and collaboration skills, with the ability to work across disciplines and teams.

Exposure to semiconductor, electronics, or RF system domains (e.g., basic understanding of circuit behavior, test data, signal integrity).

Experience working with large, complex datasets (e.g., sensor, waveform, or EDA simulation outputs).

Familiarity with data infrastructure and workflow orchestration (e.g., Airflow, MLflow, or cloud platforms).

Contributions to peer-reviewed research, patents, or open-source ML projects.