Data Scientist

Description

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.

Responsibilities

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 company—including 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.
  
  

Required Experience and Skills

• 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.

Desired Experience and Skills

• 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.

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