Artificial Intelligence Jobs in Visalia, CA

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.

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

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.

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.

The Vice President leads strategy and communications for B2B technology accounts, ensuring excellence in client service, team development, and market influence. They drive growth through integrated communications and thought leadership, while mentoring staff and overseeing high-value accounts in complex technology sectors.

Develop and deploy ML and AI imaging methods into reusable, scalable pipelines and agent-callable workflows for drug development. Collaborate with biology, clinical, and engineering teams to translate biological questions into imaging strategies, validate models for real-world and regulated settings, and integrate multimodal data for actionable insights.

Lead technical engagement for AI training and infrastructure at scale. Collaborate with engineering teams and customers to ensure successful deployment and optimization of AI/ML solutions.

Lead Responsible AI projects to detect, mitigate, and evaluate bias across GenAI, foundation models, and recommender systems. Collaborate with product and platform teams, deploy fairness interventions at scale, mentor junior engineers, and define technical strategy to align models with Pinterest policies and business metrics.

Lead and manage a team responsible for AI cloud engineering, automation, and tooling. Define automation strategies, implement Azure Cognitive Services and Databricks solutions, oversee IaC and CI/CD practices, train IT staff, partner with IT and business leaders, and foster innovation and collaboration to scale secure, production-ready analytics and ML platforms.

Design and deploy LLM-powered validation pipelines and AI integrations for silicon design toolchains. Collaborate across teams to identify AI opportunities, build productionized agentic workflows, evaluate emerging AI tech, and measure impact with data systems to improve validation, characterization, and automation of chip bring-up and verification.

Architect, build, and deploy LLM-powered AI systems and automation to accelerate post-silicon validation and toolchain workflows; integrate AI across engineering teams, evaluate emerging frameworks, measure impact, and operationalize solutions from prototype to production while supporting silicon bring-up and lab debug.

Lead architecture and delivery of an ML infrastructure efficiency platform across silicon co-design teams. Define platform contracts, onboarding, orchestration, auth, observability, storage/caching, and SLA enforcement. Own production operation, security, reliability, and performance while mentoring engineers and driving cross-team technical decisions.

Build and operate scalable backend services and data platform integrations for customer profiles, consent, personalization, campaign operations, and marketing intelligence. Design APIs, service integrations, and reusable platform capabilities; modernize database and identity systems; ensure reliability with observability, automation, and incident prevention; partner with cross-functional teams to translate business needs into production-ready solutions using AI-assisted engineering responsibly.

Lead GPU and NVLink-based cluster design and validation for large-scale AI and HPC deployments. Advise cloud partners on architectures, perform performance modeling, debug deployment issues, support NPI rollouts, and relay field feedback to engineering.

Lead customer-facing, consultative upsell efforts for AI legal solutions at law firms: drive discovery, map workflows, design demos and POCs, influence stakeholders, and partner with sales/product to close and ensure adoption.

The role involves synthesizing, placing, and routing high-speed designs, collaborating with RTL teams, and optimizing designs for power/performance area.

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.

Develop datasets, models, and evaluation systems for content safety, product security, robustness, and ML fairness for multimodal LLMs. Research and implement bias detection/mitigation, define safety metrics, contribute MLOps automation and safety tooling, and collaborate with engineers, researchers, and data scientists to improve scalable model safety and inclusivity.

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.

Lead global go-to-market and co-sell strategies with AI-native ISVs and foundational model providers. Drive joint-selling, co-marketing, pipeline management, sales enablement, and cross-functional coordination with NVIDIA product and account teams to create repeatable partnership GTM motions and measurable revenue outcomes.

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.

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.

Drive deployment of NVIDIA GPU and networking solutions at customer data centers: advise on network/compute/storage design, perform bring-up visits, debug performance, build POCs/demos, and liaise with product, engineering, and sales teams.

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 technical customer engagements to design, build, and deploy GPU-accelerated AI/ML, DL, and data analytics solutions on cloud platforms. Create PoCs, run demos, collaborate with sales and engineering, deliver workshops and technical presentations, and troubleshoot customer deployments at scale.