Skyworks is seeking a Machine Learning Engineer (MLE) to join their AI/ML team to apply cutting-edge machine learning, signal processing, and semiconductor innovation to solve real-world engineering challenges in the analog and RF domain, aiming to improve yield prediction, anomaly detection, signal classification, and device modeling.
Requirements
- 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.
- 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.
Responsibilities
- 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.
- 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.
- Work on both research-oriented prototypes and production-grade deployments.
Other
- BS and 8 years experience (Ph.D. preferred) in Machine Learning, Computer Science, Electrical Engineering, Applied Mathematics, or a related field.
- Excellent communication and collaboration skills, with the ability to work across disciplines and teams.
- Collaborate with cross-functional stakeholders including design engineers, process experts, and product owners to understand problem statements and translate them into ML solutions.
- Stay up-to-date with current trends in ML, especially those relevant to semiconductor, signal processing, or high-dimensional time-series data.
- The typical base pay range for this role across the U.S. is currently USD $91,200 - $177,200 per year.
