Artificial Intelligence Jobs in Visalia, CA

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, build, and operate end-to-end training and inference infrastructure for large language and multimodal models. Improve efficiency (memory, parallelism, kernel optimizations), ensure robust scalable training and RL pipelines, optimize low-latency/high-throughput serving (quantization, caching, speculative decoding), manage multi-GPU and multi-cloud orchestration, and productionize new algorithms with strong observability and reproducibility.

Lead as the main technical authority for NVIDIA's Federal partnership, developing AI solutions and optimizing full-stack architecture for government agencies.

The Solutions Architect will design GPU-accelerated data pipelines, develop AI workflows, and serve as a liaison between NVIDIA and OEM partners while addressing high-performance computing needs.

Design, build, and operate AWS-native AI/ML systems: RAG pipelines, fine-tuned LLMs, and microservices. Implement IaC (Terraform), CI/CD, policy guardrails, and production deployments integrating Bedrock/SageMaker, LangChain, and telemetry for secure, scalable enterprise use.

The AI Engineer will build AI-powered applications, prototype solutions, implement workflows using LLMs, and manage sub-projects while improving internal tools.

The role involves developing AI-driven compiler technologies, optimizing workflows, integrating learning systems, and collaborating on next-gen compiler capabilities for improved performance.

As a senior software engineer at NVIDIA, you will design and build tools for performance analysis of AI workloads, lead automation efforts, and enhance workflows for engineers.

Presales AI specialist designing and demonstrating AI-driven customer experience solutions. Support technical discovery, prototype deployments, integrations (APIs, real-time systems), evaluation and governance, field enablement, and transition of pilots to production while advising on architecture, model selection, and business outcomes.

Audit and ensure quality of data labeling work for ML using human-in-the-loop processes. Provide feedback, train and support annotators, monitor workflows, identify recurring issues, and help improve guidelines and processes.

Evaluate AI outputs, perform audit-based reviews, identify patterns and failure modes, apply and improve annotation/evaluation guidelines, document findings, and communicate insights to cross-functional teams to improve model performance and evaluation frameworks.

Evaluate AI model outputs, perform audit-based reviews to identify patterns and failure modes, apply and refine guidelines, document findings, and collaborate with leads and cross-functional teams to improve model evaluation and data quality.

The role involves integrating AI supercomputing systems into datacenters, collaborating with engineering teams, and producing documentation for processes related to datacenter integration and fit-out.

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.

Senior technical leader responsible for architecting production-grade AI infrastructure for media & entertainment partners. Translate business needs into scalable GPU, storage, networking and inference solutions; validate ISV integrations; influence product roadmap; engage CTO-level stakeholders; and grow a team as the vertical scales.

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.

The Staff Backend Engineer is responsible for designing and developing AI platforms, backend services, and APIs, ensuring scalability and reliability while collaborating with cross-functional teams and mentoring engineers.

As a Technical Marketing Manager, you will lead product marketing for HPE Private Cloud AI, developing impactful technical content and strategies to convey AI solutions to customers while collaborating with various teams for technical accuracy and product alignment.

Build production-ready backend components that interface directly with LLMs, create tooling to automate LLM-in-the-loop testing, design and validate LLM-based solutions using real biomedical data, and develop metrics to measure model performance and reliability under production load.

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

The role involves collaborating with customers to optimize AI workloads, leading proof-of-concepts, and developing software for NVIDIA's AI frameworks while ensuring clear communication and team collaboration.

As a Sales Executive, you will hunt for new clients, manage enterprise accounts, and create revenue streams while collaborating with internal teams.

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 Solutions Architect will design GPU-accelerated data pipelines, develop proof-of-concepts, and integrate NVIDIA's technologies with OEM partners, focusing on AI and security workflows.

Develop groundbreaking techniques to accelerate AI workloads on NVIDIA GPUs. Optimize performance of complex AI systems and collaborate with experts in the field.