Sr. Machine Learning Engineer

This is a fulltime, onsite 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 handson and focused on applying machine learning and deep learning techniques to realworld data, including largescale test, manufacturing, and signal datasets.You will work closely with crossfunctional 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 endtoend 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 LLMbased tools, where they meaningfully improve engineering productivity, analysis, or knowledge access.

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.
  
  

• Master'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 experience
• Strong foundation in computer science, algorithms, and statistics
• Proven experience developing, training, and evaluating machine learning models
• Expertise in areas such as pattern recognition, neural networks, timeseries modeling, or probabilistic methods
• Proficiency in Python and common machine learning frameworks
• Experience handling and analyzing large, complex datasets
• Strong problemsolving skills with the ability to apply ML to realworld, highimpact problems
• Ability to collaborate effectively within crossfunctional engineering teams
• Strong communication skills and ability to explain technical concepts clearly
• Experience in the semiconductor or related hightechnology industries is a plus
• Exposure to applied AI techniques such as LLMassisted analysis, retrievalbased knowledge systems, or ML workflow automation is beneficial but not required

• Practical experience with LLMs/GenAI: RAG, prompt engineering, lightweight fine-tuning, evaluation/monitoring
• Exposure 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

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