Top AI & Machine Learning Jobs

Lead enterprise Agentic AI and knowledge engineering architecture across AWS, GCP, on-premises, and hybrid environments. Design multi-agent platforms, MCP integrations, RAG and GraphRAG systems, knowledge graphs, semantic models, retrieval pipelines, and AI governance frameworks. Partner with engineering, manufacturing, data, and business teams, lead proofs of concept, evaluate technologies, establish reference architectures, mentor teams, and drive organizational adoption of AI-powered workflows.

Develop and implement AI workflows for Analog IP creation, focusing on design, optimization, and verification using EDA AI tools with a strong emphasis on collaboration with Data Science teams.

Lead design and deployment of physics-based, ML, and LLM-powered modeling solutions for semiconductor process, packaging, and manufacturing. Architect agentic AI systems integrated with modeling/design tools and fab/test platforms, improve model performance (benchmarking, RLHF, prompt tuning), and translate results into clear visual insights for diverse audiences.

Lead data analytics and ML/AI initiatives for DRAM production: data operations, automation, visualization, and decision support. Develop ML/Deep Learning/Code Assist solutions, collaborate cross-functionally, and drive large projects with sub-leadership in semiconductor manufacturing contexts.

Own product backlog and roadmap for Industrial & Physical AI; translate stakeholder needs into requirements; run hybrid agile/waterfall delivery; partner with engineering teams; manage vendors; drive UAT, rollout, and KPI reporting across global fab construction and operations.

Micron is running a Taiwan hiring event in Santa Clara to recruit for multiple senior roles across data science, smart manufacturing, process engineering, metrology, and failure analysis. Candidates should hold a bachelor’s degree in a science or engineering field, be willing to work in Taiwan (relocation support provided), and have baseline digital fluency including use of AI-assisted tools. Shortlisted applicants will be interviewed at the event; positions emphasize integrating AI-assisted tools to improve manufacturing, quality, and operational outcomes.

Design and deploy machine learning models, architect workflows, mentor engineers, and ensure scalable integration aligned with business goals.

Drive AI solution deployment for semiconductor technology. Architect AI systems, evaluate model performance, and communicate insights to stakeholders.

Lead strategic roadmap for yield smart manufacturing solutions, manage global projects, and apply AI technologies to optimize yield processes.

Partner with product owners to translate business problems into scalable data science, ML, AI, and GenAI solutions. Develop predictive, forecasting, optimization, and simulation models; analyze large datasets; build dashboards; deploy models in cloud environments; and contribute to data governance and infrastructure improvements.