AI​/ML Engineer

Hybrid 3 days onsite in Irvine, CA

Our client seeks an AI/ML Engineer to apply advanced machine learning and generative AI to semiconductor manufacturing and Customer Quality challenges within RMA-CQ and Digital Prints. The role requires building production-grade AI systems, collaborating with engineering teams, and demonstrating strong Python and PyTorch proficiency. Experience with Azure, agentic AI frameworks, RAG, and LLMs is beneficial. Candidates should show the ability to translate research into scalable enterprise solutions.

Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.

Rate: $70.00 to $80.00/hr. w2

• Design, build, and deploy production-grade AI systems for semiconductor manufacturing and Customer Quality use cases.
• Develop ML and generative AI solutions including LLM, RAG, and agentic workflows.
• Create robust Python and PyTorch components for data processing, modeling, and inference.
• Collaborate with engineering, manufacturing, and quality stakeholders to define requirements and deliver solutions.
• Evaluate architectures and document solution designs aligned to enterprise standards.
• Operationalize models with scalability, reliability, and monitoring considerations.
• Contribute to RMA-CQ and Digital Prints initiatives, including failure analysis and digital traceability.

• Proficiency in Python and PyTorch for ML and deep learning.
• Experience with Azure services for data, compute, and MLOps.
• Hands-on work with LLMs, RAG patterns, and agentic AI frameworks.
• Background applying AI/ML to physics-based or manufacturing problems preferred.
• Evidence of research translation into enterprise implementations.
• Familiarity with semiconductor, customer quality, failure analysis, or digital prints is a plus.
• Ability to pass a rigorous technical evaluation including Python coding assessment.

• PhD preferred in Electrical Engineering, Artificial Intelligence, or Computer Science with an AI/ML concentration. Master's degree with strong AI/ML experience will be considered.