Top AI & Machine Learning Jobs

Develops AI software features and services, including generative AI, LLM, RAG, semantic search, agentic, speech, and audio applications. Builds signal-processing solutions for industrial data, deploys optimized models to edge and embedded systems, and creates cloud-native AI services on AWS. Responsibilities include API and backend development, model evaluation, prompt engineering, testing, performance optimization, architecture reviews, and Agile collaboration.

Designs, develops, and deploys scalable AI and machine learning solutions across computer vision, speech, signal analytics, intelligent automation, and edge inference. Builds deep learning and multimodal models, speech-to-text systems, agentic AI capabilities, and sensor analytics pipelines. Implements AWS-based AI architectures, embedded deployments, MLOps, CI/CD, model lifecycle management, security assessments, adversarial testing, and responsible AI practices. Presents technical findings and outcomes to engineering leadership.

Designs and delivers agentic AI systems that transform complex business processes into autonomous, scalable workflows. Responsibilities include process decomposition, AI architecture, agent and tool orchestration, prompt and context strategy, prototyping, secure-by-design controls, human-in-the-loop governance, cross-functional delivery, value measurement, playbook development, and mentoring. The role requires hands-on experience with LLM-based systems, enterprise AI platforms, automation, integrations, and business process redesign.

Lead strategy and scaling of Micron Global Procurement's agentic AI ecosystem. Drive AI adoption, design enablement programs for citizen and professional developers, deliver agentic AI solutions with strong UX and measurable business value, establish governance and delivery standards, and build high-performing teams across global procurement.

Develop an AI agent for NAND product-development project execution, including project-risk detection, mitigation recommendations, workflow integration, and evaluation. The intern will study engineering workflows, prototype AI applications using generative AI, large language models, agentic frameworks, and data analytics, then deploy and document the solution while collaborating with product-development engineers and stakeholders.

Designs, develops, and deploys AI-enabled, cloud-based, full-stack enterprise applications for smart manufacturing. Integrates generative AI, machine learning, and automation into scalable business solutions; builds Angular frontends and .NET APIs and microservices; implements Azure cloud and DevOps practices; optimizes application performance and security; contributes to architecture and modernization initiatives; and mentors engineers while collaborating with stakeholders and technical teams.

Design, develop, and deploy AI-enabled enterprise applications for manufacturing efficiency, quality, and digital transformation. Build full-stack cloud solutions using .NET, Angular, JavaScript, SQL, Azure, Generative AI, and DevOps practices. Develop APIs, microservices, responsive interfaces, and intelligent automation capabilities while supporting architecture modernization, CI/CD, security, performance optimization, and cloud-native deployments. Collaborate with stakeholders and cross-functional teams, analyze system health, mentor engineers, and promote continuous improvement.

Defines end-to-end architectures for agentic AI, intelligent triage, and root-cause analysis platforms. Designs multi-agent systems, autonomous investigation workflows, human-in-the-loop controls, evaluation frameworks, and AI monitoring. Architects integrations across data, engineering, manufacturing, and AI platforms using APIs, microservices, and orchestration layers. Provides technical leadership, architectural governance, mentoring, and executive alignment while establishing standards for AI engineering, MLOps, and AgentOps.

Leads enterprise AI engineering delivery, security-by-design implementation, architecture roadmaps, governance frameworks, and global deployment. Builds and manages distributed AI engineering teams, translates business needs into high-impact technical strategies, and develops partnerships with cloud providers and AI startups. The role also represents Micron’s generative AI program internally and externally while driving standardized development practices and regulated, security-conscious delivery.

Architect scalable cloud, hybrid, and on-premise data analytics, AI, machine learning, and data science solutions for smart manufacturing. Lead architecture decisions, troubleshoot complex technical issues, collaborate across technical teams, and mentor data scientists, AI engineers, and product owners. The role requires hands-on expertise in enterprise data platforms, cloud technologies, software engineering, and emerging AI technologies.