Artificial Intelligence Jobs in San Jose, CA

Leads AI engineering enablement by developing onboarding programs, curricula, workshops, technical labs, and engineering forums. Partners with technical experts to identify skill gaps, build practical learning experiences, measure program effectiveness, and improve engineering capabilities. The role requires strong software engineering judgment, hands-on AI/ML expertise, teaching and facilitation skills, and the ability to engage senior technical audiences.

Lead AI Engineer responsible for designing, developing, deploying, and supporting scalable AI systems. The role focuses on foundation model training, LLM inference, similarity search, guardrails, model evaluation, governance, observability, and optimization. Responsibilities include improving AI system scalability, cost, latency, throughput, and hardware utilization; applying emerging research in production; and contributing to the long-term technical roadmap for foundational AI platforms.

Twelve-week, full-time AI Engineering internship focused on building agentic AI applications and scalable AI infrastructure. Interns will prototype and productionize multimodal search, document processing, autonomous workflows, model training and inference optimization, guardrails, and evaluation frameworks. The role involves collaboration with research scientists, product managers, and engineers while using technologies such as PyTorch, AWS Ultraclusters, and agentic frameworks. Applicants must be current master's students continuing their degree program.

Design, develop, deploy, and support scalable AI platform components, including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Optimize production AI systems for cost, latency, throughput, and scalability. Contribute to foundational AI strategy and roadmap while collaborating with engineering, research, product, and program teams. Lead and mentor engineers and apply emerging AI research to responsible production systems.

Design, develop, test, deploy, and support foundational AI systems, including model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Optimize large-scale AI systems for scalability, cost, latency, throughput, and hardware utilization. Collaborate with engineers, scientists, technical program managers, and product managers while shaping the technical vision and roadmap for responsible AI platforms.

Twelve-week paid PhD internship focused on researching, prototyping, and productionizing AI systems and agentic workflows. Interns will build multimodal search, document-processing, autonomous-agent, training, inference, guardrail, and evaluation capabilities. The role involves collaborating with research scientists, product managers, and engineers while using cloud infrastructure, PyTorch, and agentic frameworks to deliver scalable AI products.

Develop scalable sensor-data pipelines, physics-based models, machine-learning algorithms, predictive controls, and intelligent automation for semiconductor manufacturing. Build production-ready software, ML surrogates, and reduced-order models that integrate with manufacturing tools, control systems, and dashboards. Collaborate across physics, engineering, software, and data science teams to optimize real-time process performance and deploy innovative solutions.

Manage Japan-based autonomous trucking programs as the primary liaison between Japanese partners and U.S. engineering, product, and operations teams. Responsibilities include coordinating cross-functional execution, gathering progress data, preparing bilingual status reports, maintaining project plans and KPIs, identifying risks and dependencies, driving mitigation plans, and representing PlusAI at partner reviews and testing activities in Japan.

Leads global B2B enterprise demand generation, owning marketing-sourced pipeline, bookings, funnel analytics, AI-enabled workflows, SEO, conversion optimization, and account-based marketing. Partners with sales and revenue operations on funnel stages, attribution, scoring, routing, and performance reporting. Manages enterprise campaigns across paid media, events, webinars, content, and direct mail while building and developing the demand generation team and overseeing agencies and vendors.

Conduct computational and experimental research in fluid mechanics, heat transfer, and soft matter transport. Apply colloid and interface science, thermodynamics, electrokinetics, rheology, mathematical modeling, direct numerical simulations, artificial intelligence, and machine learning. Work independently and collaboratively, publish high-quality research, meet deadlines, and develop predictive computational tools addressing engineering grand challenges.

Leads Cisco CX AI engineering strategy and teams developing production-grade generative and agentic AI solutions. Responsibilities include architecting AI platforms, scaling data-driven systems, managing software and ML engineers, standardizing AI tools and infrastructure, partnering with product and business stakeholders, and establishing responsible AI, context engineering, and observability practices.

Architects and delivers enterprise-scale AI security systems for identity risk, anomalous access, malware detection, sensitive data classification, and threat recognition. Builds inference engines, ML platforms, feature pipelines, and production model-monitoring workflows. Provides technical leadership across multi-quarter initiatives, integrates AI with access-control and security infrastructure, evaluates emerging techniques such as LLMs and agentic systems, and collaborates across identity, threat detection, and platform teams.

Design, develop, deploy, and support foundational AI systems, including model training, LLM inference, similarity search, guardrails, evaluation, governance, experimentation, and observability. Optimize large-scale AI systems for performance, scalability, latency, throughput, hardware utilization, and cost. Shape the technical vision and roadmap for foundational AI platforms while collaborating with engineers, research scientists, technical program managers, and product managers. Lead technical innovation and influence cross-functional stakeholders.

Lead a data science team building scalable AI and machine learning solutions for customer-facing financial products. Develop and fine-tune NLP and large language models, manage model training, evaluation, validation, and production deployment, and partner with engineering, product, and design teams. Apply emerging generative AI technologies at scale while mentoring talent, translating technical findings into business outcomes, and delivering resilient systems for millions of customers.

Lead data science for AI Foundations, developing and deploying large-scale NLP, machine learning, and generative AI solutions. Partner with software engineering, ML engineering, product, and design teams to build customer-facing applications. Train, fine-tune, evaluate, and operationalize language models and other advanced models using technologies including PyTorch, AWS, Hugging Face, LangChain, and VectorDBs. Provide technical leadership, communicate complex findings, and develop team talent.

Leads firmwide adoption of AI tools in partnership with attorneys and paralegals. Translates legal workflows into scalable AI solutions, manages platform configuration, supports AI governance and risk practices, and develops communications and training programs. The role requires hands-on AI platform expertise, strong project management, legal workflow knowledge, stakeholder collaboration, and the ability to identify and address risks in AI-enabled legal work.

Leads requirements, data modeling, transaction frameworks, ETL pipelines, dashboards, and analytical reporting for payment and business systems. Partners with technology and operations teams to maintain data quality, system reliability, and production performance. Diagnoses issues, coordinates resolutions, performs statistical analysis, and contributes to future-state architecture and process improvements.

Supports business intelligence, big data, and AI/ML initiatives by analyzing requirements, developing and configuring solutions, testing applications, supporting production platforms, troubleshooting incidents, and participating in projects and continuous improvements. The role also assists with governance, change management, audits, and SOX controls while providing informal guidance to team members.

Tenure-track Assistant Professor of Marketing responsible for conducting high-quality quantitative marketing research, publishing in leading journals, teaching undergraduate and graduate marketing courses, and contributing service to the department, university, profession, or community. Preferred research areas include branding, advertising, or health marketing with applications of artificial intelligence.

Tenure-track faculty member developing an impactful robotics and AI research program, publishing high-quality research, securing external funding, mentoring students, and teaching undergraduate and graduate electrical and computer engineering courses. Responsibilities include curriculum development, interdisciplinary and industry collaboration, university and professional service, and advancing inclusive excellence. Candidates must hold a Ph.D. in electrical and computer engineering or a related field by the September 2027 start date, with demonstrated research potential and commitment to teaching and inclusive academic engagement.

Lead the design, development, deployment, and support of scalable AI systems, including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Develop optimization techniques to improve AI system scalability, latency, throughput, hardware utilization, and cost. Shape foundational AI roadmaps, collaborate with cross-functional teams, and mentor engineers while applying emerging research to production.

Design, develop, deploy, and support foundational AI systems, including model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Optimize large-scale AI systems for scalability, latency, throughput, hardware utilization, and cost. Partner with research, engineering, product, and program teams; apply emerging AI research in production; shape technical roadmaps; and lead or mentor engineering teams.

Leads enterprise AI portfolio management and transformation by prioritizing use cases, coordinating business, product, data, and engineering teams, tracking milestones and risks, establishing governance, and reporting progress and value to executives. The role also supports AI adoption, change management, organizational enablement, vendor coordination, and evaluation of emerging AI tools and workflows.

Chief of Staff to the CEO responsible for driving company priorities, building the organization’s operating cadence, managing KPI reporting, leading cross-functional special projects, and increasing executive leverage. The role requires turning ambiguous problems into measurable plans, coordinating leaders and external partners, deploying AI effectively across operations, and improving organizational efficiency in a high-growth B2B SaaS environment.

Manage strategic sales relationships with AI-native startups, drive quota attainment, qualify and close complex technology opportunities, maintain forecasts, and develop partnerships with cloud providers, system integrators, ISVs, and OEMs. The role requires positioning NVIDIA CUDA-X solutions, supporting technical and business collaborations, leading cross-functional initiatives, and expanding revenue within the startup ecosystem.