Top AI & Machine Learning Jobs

Lead product roadmap and delivery for Industrial and Physical AI solutions across construction, facilities, EHS, and manufacturing. Translate business needs into prioritized backlogs, collaborate with engineering and operational stakeholders, manage hybrid Agile/Waterfall delivery, oversee UAT, deployments, training, vendor management, and global adoption of AI/robotics/digital twin initiatives.

Develop, test, debug, document, and deploy applications for smart manufacturing solutions. Gather customer requirements, collaborate with business, product, and application development teams, train users, implement third-party solutions, and coordinate with IT procurement on contracts and support. Apply AI-enabled methods to improve application development processes while promoting Micron’s values and inclusive teamwork.

Develops and deploys AI and machine learning models for design validation, process optimization, simulation acceleration, yield improvement, and quality enhancement. Builds engineering design assistants, copilot systems, data pipelines, dashboards, and predictive models. Automates design, routing, simulation, and validation workflows while collaborating with design, simulation, and manufacturing teams to translate engineering challenges into scalable AI solutions.

Develop and maintain full-stack applications, data analytics, visualization, and reporting solutions for engineering teams. Collaborate with customers and peers to analyze needs, resolve issues, and deliver functionality. Apply modern web, database, cloud, DevOps, CI/CD, testing, observability, and AI-assisted development technologies while emphasizing maintainability, user experience, system quality, and production supportability.

Supports Technical Customer Management initiatives using AI, analytics, automation, reporting, and digital tools. Responsibilities include analyzing workflows, developing pilot solutions, building dashboards and reports, tracking customer qualification milestones and risks, improving operational processes, collaborating across technical and business teams, and measuring business impact through metrics, adoption tracking, executive reporting, training materials, and reusable workflows.

Analyze semiconductor manufacturing data to identify anomalies and improve yield; develop computer vision solutions for inspection and defect detection; build and productionize predictive models and analytical pipelines; apply generative AI, LLMs, and agentic AI to automate engineering tasks; collaborate cross-functionally, communicate insights, and mentor junior data scientists.

Manage and develop a data science team delivering production-ready analytics, machine learning models, AI tools, and what-if analyses for semiconductor manufacturing. Lead model validation, governance, monitoring, and stakeholder delivery across yield, quality, equipment efficiency, and labor productivity initiatives. Drive adoption of Generative AI, LLMs, AI agents, and emerging interoperability standards while mentoring staff, managing resources, and aligning team objectives with corporate strategy.

Develop a prototype AI-enabled equipment health monitoring and reliability analytics framework. Analyze alarms, downtime, maintenance, and performance data; create health indicators; apply statistical and machine learning methods for anomaly detection and degradation analysis; build an intelligent monitoring agent and interactive dashboard; and document and present findings to engineering stakeholders.

Design, develop, deploy, and scale enterprise AI products, agents, automations, and intelligent workflows for the People Organization. Build multi-agent systems integrating Workday, ServiceNow, Microsoft Copilot, and other enterprise platforms through APIs and event-driven architectures. Apply HR domain expertise to employee lifecycle processes, ensure secure and responsible AI governance, and implement monitoring, testing, observability, and evaluation frameworks. Partner with business and technology leaders to prototype AI solutions and drive adoption and measurable workforce transformation.

Lead a data science team to deliver cost-optimization analytics and AI solutions for procurement and manufacturing. Own model development, production deployment, monitoring, and governance. Drive adoption of Generative AI, LLMs, and agentic systems to produce measurable cost savings and integrate solutions into business workflows while mentoring staff and managing hiring and resource allocation.