Artificial Intelligence Jobs in Visalia, CA

Leads cybersecurity compliance and AI governance across NIST, CMMC, EAR, and ITAR frameworks. Maintains SSPs, POA&Ms, audit evidence, risk assessments, and compliance policies; evaluates AI vendors and use cases; embeds guardrails, access controls, data classification, logging, and review gates into LLM, MLOps, and DevSecOps workflows. Partners with engineering, security, legal, assessors, and government stakeholders to mature organizational compliance and responsible AI practices.

Build and deploy agentic and generative AI systems that automate risk and compliance investigations. Own full-stack ML systems, including data integrations, prompt tuning, orchestration, evaluation, productionization, monitoring, and transformer-based modeling across transaction, graph, text, and profile data. Collaborate with product, engineering, platform, and operations teams while leading strategic roadmaps and delivering scalable production systems.

Build and deploy agentic and generative AI copilot and autopilot systems for risk and compliance automation. Own end-to-end ML systems, including data integrations, prompt tuning, orchestration, evaluation, productionization, monitoring, and transformer-based model development. Collaborate with product, engineering, platform, and operations teams to improve fraud detection and analyst productivity. Drive strategic roadmaps and cross-functional programs with significant business impact.

The AI Executive Partner will advise C-Suite executives on leveraging AI to drive business outcomes, manage member relationships, and deliver innovative AI solutions.

Lead architecture and technical strategy for AI-driven product quality systems using LLMs and agents. Build scalable evaluation frameworks, detect regressions, generate insights, and drive cross-functional adoption while mentoring engineers and defining standards for trustworthy AI.

Lead development and implementation of AI legal and compliance frameworks. Conduct cross-functional AI reviews, maintain governance docs (model cards, impact assessments), partner with engineering on transparency and fairness requirements, build incident response and monitoring processes, and scale AI legal review workflows.

Cover California legal industry and adoption of legal tech and generative AI. Break news, produce enterprise features, cultivate sources across law firms, startups, regulators, and translate technical concepts for a professional legal audience.

The role involves designing and developing high-performance web apps, improving user interfaces, maintaining component libraries, and ensuring code quality through comprehensive testing and collaboration with other teams.

Designs, deploys, maintains, and tunes large-scale HPC and AI clusters. Responsibilities include workload scheduling, infrastructure automation, CI/CD pipelines, monitoring, logging, alerting, storage and networking deployment, bottom-up troubleshooting, methodology documentation, and R&D support. The engineer works across hardware, operating systems, GPU computing, virtualization, cloud platforms, and software stacks to deliver performant, reliable self-service infrastructure.

Develop and train large-scale multimodal foundation models (vision and language) that fuse imaging with molecular data, build scalable distributed ML pipelines for petabyte-scale datasets, and collaborate with experimental scientists and engineers to productionize models and systems.

The Principal Applied AI Engineer will lead the design of AI systems for finance, focusing on predictive modeling, intelligent automation, and software engineering best practices. They will oversee AI initiatives, mentor technical teams, and ensure compliance with financial standards and practices.

The Staff Technical Product Marketing and Partner Marketing Manager shapes product strategies and develops marketing content, drives ecosystem growth, and builds sales relationships while collaborating closely with partners to enhance brand presence and pipeline growth.

Lead deployment of NVIDIA GPU and networking solutions in customer data centers: design networks and compute/storage, debug cluster performance, run POCs, advise product roadmap, and support bring-up and customer engagements.

Embed with enterprise customers to design, build, and deploy production agentic AI workflows. Integrate platform with customer systems, handle security and compliance reviews, drive adoption and expansion, and feed product improvements based on field signal.

Embed with enterprise customers to deploy production agentic AI workflows: integrate data sources, identity, CRMs and APIs; handle security, SSO/SCIM, isolated VMs and compliance; drive adoption, instrument usage, and feed product improvements to scale deployments.

Build and lead a founding engineering team to deliver the Find, Validate, and Patch roadmap for AI-powered vulnerability discovery, validation, and remediation. Hire and grow engineers across harness/platform engineering, security research, and evaluation; partner with security and platform leadership; communicate clear engineering status.

Lead founding AI Safety & Security Engineering team, define harness architecture and engineering standards, drive Find/Validate/Patch roadmap, mentor engineers, and translate research into production-grade, secure ML systems.

Develop and formalize methods to validate reported vulnerabilities and generate/verify safe patches for internal NVIDIA targets. Define correctness, regression, and revalidation standards; produce repeatable, auditable processes and evidence. Apply AI-assisted workflows cautiously, perform bounded applied research on vulnerability classes, and document findings for independent security review.

Architect, prototype, and deploy production-grade agentic and multi-agent AI systems for Media & Entertainment. Build high-performance RAG pipelines over multi-modal assets, optimize GPU inference and TCO on NVIDIA platforms, advise customers pre/post-sale, and create reusable reference architectures, blueprints, and technical collateral to scale solutions.

Lead engineering delivery and operational health of corporate platforms (Workday ecosystem), owning integrations, security and AI enablement. Define multi-year roadmaps, build scalable AI agents and governance, set analytics/data strategy, and lead multidisciplinary teams to modernize platforms across HR, Finance, and GBS.

Lead and support AI-focused audits, investigations, and advisory reviews to detect misuse, fraud, and compliance violations. Analyze AI systems, logs, prompts, outputs, and access patterns; perform data analytics to identify anomalies; document findings and evidence; conduct stakeholder interviews; develop audit observations, playbooks, and remediation follow-up. Collaborate with technology, compliance, legal, HR, and security teams and maintain audit independence and professional skepticism.

Lead Everpure's Pull-Through strategy by securing architectural mandates with AI startups and Neoclouds, positioning Everpure as the standard data layer in large-scale LLM and RAG deployments, displacing competitors, and influencing product roadmap through cross-functional collaboration.

The role involves researching and developing GPU-accelerated AI workloads, optimizing algorithms, and collaborating with technical experts to improve hardware performance.

Serve as a technical advisor for semiconductor customers and EDA developers to GPU-accelerate EDA and manufacturing workflows, apply ML/DL for inspection and yield, analyze architectures for acceleration, deliver trainings/demos, and collaborate with product and engineering teams to deploy scalable AI-enabled solutions.

Lead strategy and execution for agentic AI product experiences across the DFIR portfolio. Define roadmaps, ship reliable and governed agentic features, drive adoption and growth, instrument metrics and experiments, run continuous discovery, and collaborate cross-functionally to ensure trustworthy, scalable AI-native products.