Sr. Machine Learning Engineer

Company DescriptionSkyworks Solutions, Inc. is at the forefront of the wireless networking revolution, developing innovative high‑performance analog semiconductors that connect people, places, and things. Serving industries such as automotive, aerospace, medical, smartphones, and IoT, Skyworks enables next‑generation wireless technologies across a wide range of markets. As a global leader, the company operates engineering, marketing, and support facilities throughout Asia, Europe, and North America. Skyworks is a member of the S&P 500® and Nasdaq‑100® indices (NASDAQ: SWKS). To learn more, visit www.skyworksinc.com.Role DescriptionThis is a full‑time, on‑site Machine Learning Engineer role based in Irvine, CA. In this position, you will design, build, and deploy machine learning solutions to address complex engineering and business challenges across design, test, manufacturing, and product domains. The role is highly hands‑on and focused on applying machine learning and deep learning techniques to real‑world data, including large‑scale test, manufacturing, and signal datasets.You will work closely with cross‑functional teams such as RF, electrical, process, product, and manufacturing engineers to translate domain problems into scalable ML solutions. Responsibilities include developing and evaluating models, performing advanced data analysis, building end‑to‑end ML workflows, and supporting deployment and monitoring in production environments. The role also involves staying current with advances in machine learning and selectively applying modern AI techniques, including LLM‑based tools, where they meaningfully improve engineering productivity, analysis, or knowledge access.QualificationsMaster’s or Ph.D. degree in Computer Science, Data Science, Machine Learning, Electrical Engineering, or a related field preferred, or a Bachelor’s degree with 5+ years of relevant professional experienceStrong foundation in computer science, algorithms, and statisticsProven experience developing, training, and evaluating machine learning modelsExpertise in areas such as pattern recognition, neural networks, time‑series modeling, or probabilistic methodsProficiency in Python and common machine learning frameworksExperience handling and analyzing large, complex datasetsStrong problem‑solving skills with the ability to apply ML to real‑world, high‑impact problemsAbility to collaborate effectively within cross‑functional engineering teamsStrong communication skills and ability to explain technical concepts clearlyExperience in the semiconductor or related high‑technology industries is a plusExposure to applied AI techniques such as LLM‑assisted analysis, retrieval‑based knowledge systems, or ML workflow automation is beneficial but not requiredDesired Experience and SkillsPractical experience with LLMs/GenAI: RAG, prompt engineering, lightweight fine-tuning, evaluation/monitoringExposure to semiconductor / electronics / RF domains (test data, signal integrity, circuit behavior)Experience with large, complex datasets (sensor, waveform, or EDA simulation outputs)Familiarity with data/ML infrastructure and orchestration (e.g., Airflow, MLflow, cloud platforms)Publications, patents, or open-source ML contributions