Artificial Intelligence Jobs in Sunnyvale, CA

Verify chip-level and performance behavior of custom ASICs: design end-to-end test flows with architecture team, run simulation-based verification, implement UVM environments, use constrained-random and functional-coverage methodologies, and coordinate vendors/contractors.

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

Lead Applied AI product initiatives for mobile games by identifying gameplay opportunities, defining AI-driven roadmaps, translating between game design and ML teams, setting mixed technical and game success metrics, and partnering with central tech teams to deploy ML features that improve fun and retention.

Manage AI compute clusters, monitor systems health, optimize resources, and troubleshoot technical issues, ensuring high performance for ML applications.

The CX Manager will own the ERP integration domain, providing problem-solving expertise for complex customer issues and ensuring efficient issue resolution related to ERP systems and AI operations.

Lead AI initiatives, establish strategy, and develop generative AI applications. Collaborate with teams to build and optimize financial products.

Translate multi-modal AI research into 0-1 products: design and run ML experiments, build scalable training and evaluation infrastructure, implement MLOps and data pipelines, deploy models, and use AI code tooling to move experiments to production MVPs.

As a Backend Engineer at Brain Co., you will design, build, and operate backend services and data pipelines for AI products, focusing on robustness and scalability. You'll collaborate across teams and own the full service lifecycle while ensuring high availability and performance. You should have 3+ years of experience in production backend systems and a strong foundation in APIs and distributed systems.

As an AI Product Engineer, you will develop and deploy AI-driven software solutions, collaborate with customers, and optimize applications for real-world impacts.

The AI/ML Engineer will design and deploy advanced AI models, optimize performance, and directly engage with government officials to transform industries through innovative AI solutions.

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.

As an AI Engineer, you will develop new AI products, iterate with a small team, and apply various GenAI techniques to enhance educational experiences.

The intern will design and implement AI solutions for manufacturing workflows, focusing on LLMs to improve operational efficiency, data management, and collaboration across teams.

The Software Engineer will build AI-powered chatbot workflows, own features end-to-end, and collaborate in a fast-paced environment. Ideal candidates have a strong engineering foundation and experience with AI development tools, focusing on enhancing software processes.

Lead the optimization and performance analysis of distributed training and inference workloads on NVIDIA GPU platforms, with responsibilities including debugging, benchmarking, and ensuring reliability of large-scale AI systems.

Drive benchmark results for GenAI inference, optimize performance across multiple models, and establish methodologies while leading technical initiatives in GPU performance engineering.

Lead technical performance analysis and optimization of large-scale AI/HPC clusters. Diagnose cross-component bottlenecks, build and maintain benchmarking suites, collect and transform telemetry into time-series dashboards, and collaborate with engineering, field teams, and customers to resolve configuration and performance issues.

As a Senior Applied AI and AI Infrastructure Engineer, you will manage AI projects, deploy infrastructure, mentor junior engineers, and apply AI for chip design.

The Investor role at Samsung Next focuses on sourcing and evaluating early-stage investments in AI and robotics. Candidates will develop investment skills under experienced guidance, participate in deal discussions, and support startup founders. A technical background in related fields is essential, along with strong analytical and communication skills.

The Director of Engineering - AI will lead the development and deployment of AI-driven SaaS solutions, mentor engineers, and ensure scalable ML infrastructure while collaborating with cofounders and stakeholders.

Build and productionize internal AI-powered tools and data systems. Implement and maintain infrastructure, data pipelines, deployments, monitoring, and access controls. Integrate third-party AI services, ensure data quality, document systems, and collaborate with stakeholders to deliver maintainable solutions.

The Growth Lead will drive the go-to-market strategy and user acquisition for an AI-powered SaaS product targeting SMBs, focusing on growth from launch to scale via effective user engagement tactics.

Lead the go-to-market strategy and execution for a new AI-powered consumer product, focusing on customer acquisition through various channels and optimizing performance metrics.

Seeking a hands-on Growth Lead to launch and drive user acquisition for a new consumer AI product, with ownership of growth strategies and metrics.

The Growth Associate & Product Launch Coordinator will support the launch of an AI consumer product, focusing on user acquisition, go-to-market planning, and onboarding improvements while working with the Head of Growth and product team.