Top Tech Jobs & Startup Jobs in Seattle, WA

Own end-to-end software integration across firmware, BSP, drivers, GPU software, services, and release systems. Lead system-level debugging of boot failures, crashes, resets, power transitions, performance regressions, and update issues. Analyze logs, traces, crash dumps, and hardware diagnostics to identify root causes, automate failure classification, integrate partner software, and coordinate cross-functional resolution across firmware, kernel, hardware, architecture, and OS teams.

Analyze GPU application performance and design, implement, and integrate MLIR/LLVM compiler optimizations and passes. Collaborate with hardware, compiler, and application teams, engage with open-source LLVM community, and enable best-in-class performance for AI and HPC workloads.

Develop and debug cloud-native solutions for AI/ML datacenters, focusing on Kubernetes and Slurm enhancements and customer workflows.

Leads site reliability operations and Tier 3 enterprise support across identity, messaging, compute, endpoints, databases, networking, and datacenter infrastructure. Owns incidents, SLAs, compliance, vulnerability remediation, asset management, root-cause analysis, automation, and permanent fixes. Provides technical leadership and mentoring, supports executives, coordinates with global platform teams and vendors, leads site projects and major incidents, and represents local priorities in regional and global IT initiatives.

Develop and guide sensor fusion functionality for autonomous driving by creating 3D world models and ensuring accurate representations using various signals. Lead technology approaches and mentor team members while adhering to automotive quality standards.

Define system and technical requirements for fault-tolerant quantum computing across hardware, software, and firmware. Develop real-time quantum error correction and calibration approaches, perform systems analysis across qubit modalities, and create and review test cases. Collaborate with product, research, engineering, and external partner teams to advance quantum control systems, quantum computing products, and related NVIDIA technologies.

The Senior LLVM Compiler Engineer will contribute to upstream LLVM development, lead design discussions, and ensure high-quality compiler solutions in collaboration with open-source communities.

Develop platform software using container runtimes and Kubernetes to enable GPU-accelerated applications. Build GPU resource support for container orchestrators, integrate software across NVIDIA’s technology stack, and contribute to cloud-native systems. The role requires systems programming, Linux internals, distributed systems, cloud computing, and performance, security, and reliability expertise. Responsibilities include solving complex problems, managing multiple priorities, and collaborating across engineering teams.

Develop Rust-to-GPU compiler pipelines, custom intermediate representations, optimizers, and ahead-of-time, just-in-time, and link-time compilation tooling for NVIDIA GPUs. Design Rust-based safety abstractions across GPU execution boundaries and expose low-level CUDA hardware features. Responsibilities include compiler architecture, GPU code generation, debugging, profiling, benchmarking, and independently driving complex engineering initiatives from research through production.

Design and implement GPU compiler components, optimize compiler performance, solve graphics and parallel-computing compilation problems, collaborate with GPU driver and architecture teams, contribute to LLVM and DXC open-source projects, and help define SPIR-V extensions and standards.