Top AI & Machine Learning Jobs

Design, pretrain, fine-tune, and deploy large-scale LLMs and agentic AI solutions using unstructured and multimodal data. Build prototype-to-production GenAI systems with MLOps, Databricks/MLflow, and cloud infrastructure (Azure). Collaborate cross-functionally, troubleshoot, document, and mentor junior engineers while presenting solutions at scale.

Design, develop, and deploy ML and AI analytics for PLM, BOM, and lifecycle risk using large enterprise datasets. Integrate Teamcenter and SAP data, build scalable Databricks/Spark solutions, create Tableau dashboards, lead projects, mentor junior staff, and enable data-driven product and release decisions.

Lead and execute NPI projects from planning through implementation. Create and maintain schedules, coordinate cross-functional resources, manage costs and procurement, provide technical and process expertise, resolve project issues, and deliver status and deployment readiness for equipment and programs.

Develop, evaluate, and integrate computer vision and deep learning algorithms for semiconductor equipment. Engage with customers to define needs and transfer lab features to fabs, provide technical escalation support, and collaborate with cross-functional teams to improve sensitivity, stability, and system-level integration.

Lead research, design, prototyping, implementation, and optimization of computer vision and deep learning detection algorithms for optical wafer inspection. Perform feasibility studies, literature review, data analysis, and support software integration and evaluation to improve detection performance and reduce computational cost.

Develop, integrate, and support metrology eBeam (SEM) algorithms for R&D and customer sites. Build computer vision, machine learning, and deep learning solutions, provide diagnostics and bug fixes, collaborate across applications, systems, and physics teams, and support customer deployment and training with up to 30% travel.

The Data Scientist will develop AI-driven solutions for supply chain efficiency using machine learning, statistical modeling, and advanced analytics. Key responsibilities include designing scalable data pipelines, collaborating across teams, and exploring emerging technologies.

Lead design and implementation of agentic and multi-agent AI systems for manufacturing and enterprise use. Build scalable AI platforms (orchestration, RAG, vector/graph DBs, knowledge graphs), mentor teams, drive AI governance, prototyping, and production deployments to deliver measurable business value.

Partner with HR COEs to identify and prioritize AI use cases, evaluate and optimize Workday and AiMEE capabilities, lead pilot deployments, collaborate with data science and GIS teams to build HR analytics and AI solutions, and support planning, testing, and deployment to improve employee experience and process automation.

Develop and deploy end-to-end AI/ML solutions focused on GenAI and LLMs. Build and fine-tune models, create embedding search and agentic systems, perform forecasting and data mining, collaborate with stakeholders, and drive improvements in supply chain and material demand forecasting.