Top Tech Jobs & Startup Jobs in Seattle, WA

Lead and grow a software engineering team responsible for CUDA Math Libraries platform expansion and readiness. Own integration, qualification, compliance, validation, performance testing, defect triage, and technical roadmaps across specialized platforms. Collaborate with library, DevOps, QA, compiler, CUDA, release, and platform teams. The role requires hands-on high-performance numerical software development using C++ and Python, parallel computing, performance optimization, and software engineering leadership.

Lead technical partnership with Alphabet teams to drive adoption and integration of NVIDIA libraries, models, and frameworks. Coordinate cross-functional engineering and GTM teams, resolve integration challenges, influence product roadmaps, and deliver joint solutions that accelerate partner workloads and developer adoption.

Lead HBM and LPDDR system integration and bringup for next-generation SoCs. Own memory performance, power, thermal, and reliability closure across silicon, package, board, and firmware. Drive post-silicon margining, VF shmoo, eye characterization, and correlation. Debug training, calibration, SI/PI, and system stability issues. Define validation, characterization, and issue-tracking plans to produce production-ready operating points.

Architects and develops datacenter power and performance-management software, including real-time controllers, dynamic provisioning, power policies, and hardware-software interfaces. Responsibilities span architecture, pre-silicon validation, silicon bring-up, productization, deployment, and production support. The role investigates complex firmware, driver, hardware, and platform issues; develops validation automation; and collaborates with GPU, ASIC, firmware, driver, and datacenter systems teams to optimize performance, power, thermal behavior, reliability, and energy efficiency.

The role involves architecting and operating NVIDIA's cloud-native attestation platform, developing high-availability services, collaborating with cross-functional teams, and mentoring engineers.

Design, develop, integrate, test, and productize perception software for autonomous driving systems. Responsibilities include implementing robust and reusable software components, deploying deep neural network models to embedded real-time platforms, developing verification plans, debugging systems, maintaining documentation, and analyzing real or synthetic benchmark data. The role requires close collaboration with perception engineers and researchers throughout the software development lifecycle.

Leads multifunctional initiatives defining safety architectures and requirements for autonomous vehicles. Develops safety concepts and analysis supporting continuous software delivery, improves safety metrics and analysis tools, evaluates safety data, and communicates readiness results. Collaborates with perception, AI, motion planning, and architecture experts to ensure DRIVE products meet rigorous safety standards.

Leads NVIDIA’s Infrastructure Security Engineering organization for EDA clusters. Builds and operates security controls across compute, storage, and networking in on-premises and multi-cloud environments while preserving performance for long-running workloads. Owns the technical roadmap, security technology lifecycle, automation, instrumentation, compliance evidence, and cross-functional execution. Develops secure-by-default infrastructure and leads teams responsible for scalable enforcement, observability, mitigation, and security outcomes.

Design and implement LLM-first APIs and documentation for CUDA-X math libraries. Develop tools, metrics, and processes to improve AI-agent code generation and transform library APIs into LLM-friendly formats. Collaborate with stakeholders on LLM-enhanced releases while prototyping solutions for code-generation platforms. Requires expertise in LLMs, fine-tuning, reinforcement learning, RAG, MCP, agent tooling, composable API design, and technical documentation.

Develop and lead production software-defined networking for NVIDIA’s global GPU cloud infrastructure. Design multi-tenant control and data planes using Open vSwitch, OVN, OpenFlow, Kubernetes, C, and Go. Build networking services, plugins, automation, testing, observability, and reliability improvements. Lead architecture and code reviews, mentor engineers, support on-call operations, and resolve complex production incidents through diagnostics and source-level debugging.