Top Tech Jobs & Startup Jobs in Seattle, WA

Design and implement Rust-to-GPU compiler backends, IR frameworks, and JIT/AOT toolchains. Lower Rust AST/MIR to MLIR/LLVM/PTX, build GPU-specific optimizers, enforce safe parallel abstractions across host/device boundaries, and expose ergonomic device-side primitives. Drive projects from research to production and support profiling, debugging, and benchmarking workflows.

Lead distributed engineering and data teams to build NVIDIA's end-to-end data curation strategy for autonomous vehicles. Architect scalable systems and pipelines to mine, classify, and surface valuable driving scenarios from massive real and simulated datasets. Collaborate with research, perception, mapping, simulation, and fleet teams to deliver high-quality data, champion metadata and quality standards, and drive continuous AV performance improvements.

Lead performance and scalability analysis of the Kubernetes-based accelerated runtime stack, design upstream control-plane changes for hyperscale clusters, optimize container startup and inference latency, advance confidential container performance, model large AI-factory deployments with simulations, build at-scale tests and monitoring, and collaborate with researchers and upstream communities to validate and publish results.

Lead and manage a team of Technical Program Managers to deliver DGX Cloud core infrastructure programs (network, storage, security, trust services, telemetry, break/fix). Drive cross-functional alignment with engineering, product, operations, and cloud providers; establish operating rhythms, risk tracking, metrics and dashboards; coordinate operational readiness and incident response; and standardize TPM practices to improve reliability, scalability, and customer readiness.

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.

Join the Compute Compiler Team to align NVIDIA's compiler codebases with open-source projects (LLVM/Clang/MLIR), build tooling and workflows for large-scale codebase reconciliation, and develop automation and AI-assisted developer tools to improve productivity, validation, and refactoring across distributed teams.

Design, implement, and productionize state-of-the-art deep learning and computer vision models for autonomous vehicles. Define and collect training datasets, build training pipelines and real-time inference runtimes, collaborate with researchers to turn experiments into robust, deployable systems, and optimize architectures for multi-sensor fusion and efficient deployment.

The role involves defining architecture for NVLink Fusion, collaborating with customers, mentoring teams, and managing software abstraction layers.

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

Lead strategic AI platform initiatives, define product vision, drive clarity in cross-functional engagements, and improve developer productivity by delivering AI-powered capabilities.