Artificial Intelligence Jobs in Santa Clara, CA

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

Perform Chinese annotation, labeling, and quality review of multimodal datasets (text, image, video, audio) for generative AI. Evaluate AI prompts/responses, conduct QA, identify edge cases, refine guidelines, and collaborate with teams to improve annotation workflows and tooling.

Lead and manage a team of Chinese (zh-CN) multimodal annotators and reviewers to meet throughput and quality targets. Own guidelines, calibration, audits, reporting, onboarding, and cross-stakeholder coordination for multimedia labeling workflows.

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 outputs, perform audit-based reviews, identify failure modes and trends, apply and refine guidelines, communicate findings, participate in calibrations and stakeholder syncs, and help improve evaluation frameworks for human-in-the-loop AI.

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.

Build and scale AI data and ML infrastructure: evaluation systems, fine-tuning pipelines, agent-first product surfaces, high-throughput data workflows, and integrations of new models into production.

Rapidly prototype and iterate AI-powered features (LLMs, embeddings, real-time audio, APIs), lead experiments from hypothesis to proof-of-concept, collaborate with product and engineering to translate prototypes into product-aligned solutions, and share learnings and artifacts to accelerate team innovation.

Design and scale the infrastructure for Fury's AI model training and deployment, ensuring efficient data pipelines and collaboration with AI teams.

Lead technical product marketing for AI compute, owning positioning, competitive strategy, and technical content. Translate systems-level innovations into customer and executive narratives, drive competitive intelligence, support launches, and lead a technical product marketing team aligned with product, engineering, and sales.

As a Founding Perception Engineer, you will develop 3D perception systems for autonomous machinery, integrating various sensors and leading field testing. This role focuses on real-world applications in construction, addressing challenges unique to harsh environments.

The SF Launch Lead will drive expansion in the tech market, build a candidate base, onboard companies, and oversee the go-to-market strategy.

As a Founding Engineer, you'll develop infrastructure for an AI platform, including AI agents, secure systems, and SDKs for integration.

Design and deploy AI agents and workflows, integrate complex solutions into the Beacon platform, and serve as a technical advisor with a focus on business needs.

You will develop AI systems for medical diagnosis, focusing on clinical accuracy and safety. Responsibilities include optimizing LLM integration and architecting AI infrastructure.

Join as a founding engineer to build a proactive AI mentor. Design memory systems, adaptive interfaces, and evaluate AI behavior change, directly impacting user growth.

As a Founding Engineer at Fig AI, you'll build AI agents for food manufacturers, architecting systems, and develop products from idea to execution.

The role involves designing, building, and deploying production-grade AI agents to automate real estate workflows, managing the entire product lifecycle from prototype to production.

Drive revenue expansion as the first commercial hire in a startup, scaling a productivity platform into enterprise markets, managing sales cycles, and developing strategies to achieve growth targets.

As the second engineer, you will build backend systems for browser automation, collaborate with founders, and design secure authentication processes.

As an Applied AI Engineer, you will develop world generation pipelines, design orchestration systems, and create reinforcement learning frameworks for gaming.

As a Solutions Architect at NVIDIA, you'll develop and deploy AI systems, optimize performance, and collaborate with partners to integrate AI solutions into enterprise environments.

Lead NVIDIA's storage strategy for AI Cloud, focusing on high-performance storage solutions for critical workloads, mentoring engineers, and influencing technical direction across teams and external partners.

Design and implement AI-driven optimizations for software development workflows, leveraging LLMs and Agentic AI to enhance productivity and reliability.

The Principal Software Research Engineer will lead research in distributed systems, develop innovative solutions, interface with sponsors, and transition research to product development while managing project proposals and reports.