Machine Learning Modeling Winter/Spring Co-Op (Jan-June '27)
A six-month co-op (Jan–June 2027) at Skyworks Solutions in Irvine, CA, where the intern builds and optimizes machine learning models — including ANNs and LLM-powered agents — to support acoustic/RF semiconductor device design and manufacturing analytics. Core stack: Python, PyTorch/TensorFlow, NumPy/Pandas/Scikit-learn, with some cloud exposure.
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Internship
- Experience
- Not specified
- Category
- Ml / AI
- Posted
Skills
Must have
- Currently pursuing an M.S. or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, Data Science, or related technical field
- Solid foundation in machine learning, deep learning, statistical modeling, and data analysis techniques
- Proficiency in Python programming
- Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or Keras
- Familiarity with data analysis/scientific computing libraries: NumPy, Pandas, Scikit-learn
- Basic knowledge of cloud computing platforms such as AWS, Azure, or GCP
- Experience developing ML workflows, data pipelines, or scalable software solutions through coursework, research, or projects
- Strong analytical and problem-solving skills, attention to detail, ability to work independently
- Self-motivated learner with a passion for AI, innovation, and continuous professional growth
Nice to have
- Experience with C++ and SQL
- Coursework or project experience in LLMs, generative AI, agent-based systems, or deep learning applications
- Coursework or project experience in RF, microwave engineering, signal processing, computational electromagnetics, or semiconductor devices
- Experience with simulation-generated datasets and physics-based models (PINNs, surrogate modeling, digital twins)
- Familiarity with scientific computing, numerical optimization, and surrogate modeling techniques
- Familiarity with reinforcement learning, Bayesian optimization, or other optimization techniques for engineering applications
- Interest in applying AI/ML to engineering design automation, semiconductor technologies, and manufacturing optimization
- Familiarity with Git, Jira, and MLflow for version control and model management
Full description
DescriptionSkyworks is a global leader in wireless connectivity, delivering cutting-edge RF, acoustic wave, and semiconductor technologies that power next-generation communication systems. As we continue to expand our artificial intelligence and machine learning capabilities, we are leveraging advanced analytics and data-driven approaches to accelerate innovation, optimize manufacturing processes, and enhance product performance.
We are seeking a highly motivated Machine Learning Modeling Engineer Intern to join our Acoustic Device Group. In this role, you will develop, implement, and optimize machine learning models to support the design, analysis, and development of advanced acoustic and RF devices. You will work with complex engineering datasets and collaborate closely with multidisciplinary teams to apply AI and machine learning techniques to real-world semiconductor challenges.
The ideal candidate has strong analytical and problem-solving skills, a solid foundation in machine learning algorithms and data science, and a passion for applying AI technologies to RF, acoustic wave, and semiconductor engineering. This position offers a unique opportunity to contribute to next-generation wireless products while gaining hands-on experience at the intersection of machine learning and advanced semiconductor technology.
Co-Op Period from January to June 2027
Responsibilities
- Apply artificial neural network (ANN) and machine learning techniques to support microwave CAD and semiconductor design projects.
- Develop and evaluate ANN-based models for acoustic devices, electromagnetic (EM) analysis, and parametric modeling.
- Assist in the development of data-driven models for RF filter design and performance prediction.
- Support neural network-based multiphysics modeling of electrical, acoustic, thermal, and mechanical interactions.
- Collect, clean, and preprocess structured, unstructured, time-series, and image datasets for machine learning applications.
- Perform exploratory data analysis (EDA), feature engineering, and data visualization to improve model accuracy and insights.
- Build and optimize LLM-powered agents with capabilities such as tool integration, workflow automation, and multi-step reasoning.
- Research emerging developments in AI, machine learning, and data science, and explore their applications in semiconductor design and manufacturing optimization.
Required Experience and Skills
- Currently pursuing an M.S. or Ph.D. degree in Computer Science, Electrical Engineering, Applied Mathematics, Data Science, or a related technical field.
- Solid foundation in machine learning, deep learning, statistical modeling, and data analysis techniques.