Artificial Intelligence Jobs in Sunnyvale, CA

Design and build an AI-driven account management and optimization platform using LLMs and agentic systems. Create diagnosis and recommendation models, ensure reliable long-running services with observability and safeguards, and collaborate with ad delivery and product teams to improve advertiser performance and revenue.

Manage and curate the AI models portfolio, collaborate on model launches, evaluate model quality, and drive product marketing initiatives.

As a founding Solutions Engineer, you will lead technical discovery, run POCs, and ensure successful customer integration while collaborating with product and revenue teams.

As a Senior Software Engineer at Tenstorrent, you will develop AI compiler technologies, optimize computational graphs, and enhance MLIR frameworks to connect AI models with hardware.

The Physical Design Engineer will lead efforts in solving physical design challenges, improve RTL-to-GDS methodologies, and integrate AI/ML solutions into CAD flows, focusing on performance and runtime improvements.

Lead AI feature design and delivery, build large-scale ML systems, mentor engineers, and define best practices across the engineering organization.

Drive end-to-end LLM inference performance on Intel GPUs: profile bottlenecks, write and optimize custom GPU kernels (attention, MoE, quantization, fusions), upstream improvements to vLLM/SGLang/PyTorch, and collaborate with architecture and compiler teams to shape hardware roadmaps.

Lead synthesis, placement, routing, and full-chip physical design for high-speed AI silicon. Perform block and full-chip physical verification, timing closure, power/performance/area optimization, DRC/LVS and IR/EM resolution, STA and constraint drafting, floorplanning, and script-based flow enhancements. Collaborate with RTL teams to integrate blocks into the full-chip architecture.

Owns end-to-end technical programs for site and data center operations supporting AI cloud and customer deployments. Single-threaded owner across hardware, AI cloud, network/storage, and facilities; drives site readiness, installation, commissioning, incident reviews, KPIs (availability, MTTR/MTTD, capacity), executive dashboards, governance, and risk tracking.

Lead Cerebras's model portfolio: decide which models ship, set quality standards and benchmarks, partner with model labs and open-source maintainers, drive model launches, enable customers, prioritize optimizations, and coordinate cross-functional teams to maximize inference performance and adoption.

Own realtime product marketing for Cerebras inference: create technical content, benchmarks, demos, and influencer/community programs; set editorial direction; identify competitive edges and drive organic growth among developers and AI builders.

Architect and drive a unified, self-service inference control plane and reliability practices for large-scale multi-datacenter and cloud inference fleets. Build capacity orchestration, rollout safety, observability, SLO-based reliability, incident response, and automation; mentor senior SREs and measure impact through reduced toil, faster deployments, and SLO compliance.

Design, build, and optimize distributed PyTorch training systems for multi-node GPU clusters. Profile and eliminate performance bottlenecks across data pipelines to GPU kernels, implement low-level CUDA/cuDNN/Triton kernels, tune CPU/GPU/memory/network utilization, and develop monitoring and debugging tools for large-scale training runs.

Own strategy and execution for a portfolio of AI-native and hyperscale customers. Serve as primary relationship owner, drive revenue, market share and product adoption, coordinate with solution architects, product marketing, OEMs and partners, forecast and train customers, and evangelize NVIDIA platforms to accelerate enterprise growth.

Lead product strategy and lifecycle for local AI system software, tools, and apps. Drive customer discovery, define requirements, coordinate cross-functional teams, set KPIs, and support go-to-market to increase adoption of local AI solutions.

Lead design and delivery of SMAC workflow methodology and infrastructure to keep system specifications and manufacturing test specs aligned. Build production-grade Python pipelines, automated checks, CI gates, and agent-ready tooling that detect spec drift pre-silicon. Integrate workflows into program milestones, drive cross-org adoption across design, operations, and DFX, and apply AI where appropriate while ensuring reviewable, auditable artifacts.

Lead product marketing for Azures cloud and AI platform to define category strategy for agentic applications, build executive narratives, drive technical marketing frameworks, scale demo platforms, enable field and partners, and lead a high-performing PMM team to deliver market leadership and cross-platform adoption.

Work as an early-career full-stack software engineer building and maintaining web application features across backend, frontend, APIs, data, tests, and internal tooling. Use AI-assisted development tools responsibly, write maintainable code and tests, participate in code reviews, and learn product and customer context to deliver production-quality outcomes.

Build, train, evaluate, and deploy production computer vision models (detection, segmentation, OCR, barcode decoding, visual search). Own dataset quality, tooling, model releases, inference exports, and monitoring. Collaborate cross-functionally to improve model performance, robustness, and deployment for retail robotics and edge environments.

Research and develop GPU-accelerated techniques for AI and financial workloads. Analyze and optimize performance on CPU/GPU architectures, collaborate with industry and academia, publish findings, and influence hardware and software design while supporting developer adoption.

Design and implement AI-native frameworks, optimize performance for deep learning models, and ensure high-quality software development using modern C++ and AI tools.

As a Senior Full-Stack Software Engineer, you will design, build, and ship AI-powered systems to optimize workflows in the single family rental market, focusing on backend services and full-stack development in a fast-paced environment.

As a Senior Software Architect for AI Networking, you'll design and implement AI networking technologies, optimize data processing in AI systems, and collaborate on cutting-edge solutions.

Build and scale backend infrastructure for Ambient AI in healthcare. Work across real-time clinical documentation, AI-driven billing automation, and clinical intelligence. Ship production systems, collaborate with clinicians and customers, maintain reliability, monitoring, and metrics, and operate across the full software stack.

The Founding AI Engineer will design and build an AI-native compliance platform, handling complex financial data and developing scalable backend services, while establishing processes for enterprise readiness.