Artificial Intelligence Jobs in Visalia, CA

Leads enterprise AI-focused sales campaigns across a regional territory, advising C-suite and technical AI buyers on data platform and infrastructure solutions. Partners with account executives, solution architects, engineers, product teams, GSIs, and channel partners to develop use cases, reference architectures, ROI frameworks, and joint go-to-market strategies. Owns pipeline discipline, forecasting, account planning, complex deal orchestration, and AI solution positioning for enterprise workloads.

Embed with customers to learn their workflows, redesign and build production GenAI/LLM systems on AWS, ship and operate code, evaluate non-deterministic models, and own business outcomes.

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

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.

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.

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.

The role involves designing and implementing integration solutions using iPaaS technologies, managing development processes, and mentoring team members while ensuring client satisfaction.

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.

Design and implement an MLIR-based AI compiler for GPU inference: develop graph representations and dialects, optimize performance and memory, define APIs, generate kernels, and collaborate with framework and hardware teams to enable new model patterns and GPU features.

As a Senior Solutions Architect, you will assist customers in building solutions with NVIDIA's AI technology, focusing on Generative AI and Large Language Models while collaborating across teams for performance analysis.

Lead and deliver large, high-risk HPC and AI deployments across the Americas. Manage customer relationships, project financials and P&L, cross-functional teams, schedules, legal/commercial issues, and on-site acceptance. Mentor team members and provide performance input while coordinating internal and external resources.

Architect and demonstrate simulation workflows using DSX Sim and Omniverse libraries to help partners and customers build, validate, optimize, and operationalize AI factory digital twins. Drive integration of Omniverse libraries, develop reference architectures, prototypes, benchmarks, and sample workflows, and coordinate with sales, product engineering, and partners to resolve blockers and advance adoption.

Advise ISVs on designing, deploying, and optimizing large-scale accelerated AI infrastructure. Lead architecture reviews, POCs, benchmarks, and production deployment guidance across compute, networking, storage, containers, orchestration, observability, and CI/CD. Create reference architectures, sizing guidance, technical playbooks, demos, and whitepapers. Support cluster monitoring, reliability, and performance improvements. Up to 20% travel for customer engagements.

Design and scale Kubernetes-native, GPU-accelerated cloud architectures for large-scale robotics simulation, synthetic data pipelines, training, and inference. Advise partners, optimize scheduling, storage, networking, and GPU utilization, and drive adoption of NVIDIA Physical AI frameworks while collaborating with product and engineering teams.

Develop and implement compiler optimization algorithms for deep learning workloads, analyze networks, debug and profile GPU performance (CUDA), define public APIs, and deliver ahead-of-time and just-in-time compilation techniques for NVIDIA GPUs to improve inference performance, build times, and memory efficiency.

Founding technical role to design, build, and deploy internal AI tools and agents using LLMs and retrieval systems. Partner with investors and the data team to accelerate sourcing, diligence, portfolio insights, and define CRV's AI strategy through rapid prototyping and production-grade systems.

The Technical Account Manager will lead customer technical projects, provide architecture guidance, ensure product adoption, and serve as a trusted advisor to enhance customer success and satisfaction.

Research, design, and train foundation models for robotics; align text-based reasoning with low-level control policies; evaluate zero-shot generalization; run experiments; integrate models into robotic systems and present findings externally.

Design and architect multi-agent orchestration frameworks, build tool-calling pipelines and reasoning loops, and optimize latency and token usage for real-time agentic workflows and autonomous operations.

Run adversarial tests on language and multimodal models, build guardrails and real-time filters for autonomous tool use, and support RLHF alignment and constitutional AI development to ensure safe AI deployment.

Lead product strategy and roadmap for AI and robotics products, translating VLA and agentic RAG breakthroughs into customer value, defining safety/usability/performance metrics, working with enterprise adopters, and driving cross-functional delivery.

Optimize, compress, and distill large language and vision models for on-device inference. Build pipelines for distillation and hardware-specific compilation, and benchmark performance across NPU/GPU architectures.

Design, orchestrate, and optimize large-scale LLM pre-training across 1,000+ GPUs. Implement 3D parallelism, manage GPU clusters (SLURM/Kubernetes), optimize InfiniBand/RDMA networking and memory, and automate checkpointing and failure recovery for long training runs.

Develop multimodal intent-recognition models from gaze, gesture, and voice; implement socially aware navigation respecting personal space; design robot visual and auditory UI feedback; run user studies and rapidly prototype AI-driven voice and visual interfaces.