Top Tech Jobs & Startup Jobs in Seattle, WA

As a Senior Deep Learning Systems Engineer, you will optimize datacenters for AI applications by analyzing performance metrics and developing software tools.

Design, develop, test, and optimize system software for next-generation ARM SoCs in pre- and post-silicon phases. Analyze system-wide performance bottlenecks, recommend HW/SW policies, perform competitive workload comparisons, and drive full-stack adoption of performance optimizations across NVIDIA software and OSS SDKs.

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 core components of the CUTLASS platform, contribute to the MLIR-based backend compiler stack, and author example kernels while collaborating with GPU architecture teams.

The role involves benchmarking deep learning models on NVIDIA GPUs, improving software performance, and developing automation tools for performance optimization.

Lead cross-functional programs to deliver on-prem and cloud-integrated DGX Cloud infrastructure: drive large-scale bare-metal fleet bring-up, automation, software integration, capacity operations, roadmap alignment, program governance, and metrics-driven operational reviews. Partner with NCPs and internal engineering, SRE, and data center teams to establish validation, bootstrapping, and maintenance workflows for production-ready clusters.

Drive large-scale DGX Cloud infrastructure programs with CSPs and NVIDIA Cloud Providers. Define requirements for compute, storage, networking and GPUs; build roadmaps, KPIs, and PLC milestones; manage capacity operations, risk mitigation, and engineering deliverables using program management tools; and influence partner alignment for deployment, security, and observability.

Build and optimize quantized and sparse inference recipes for LLMs, implement performant kernels and model-level changes in inference engines, own model export pipelines, develop benchmarking and numerics-debugging tools, improve developer productivity (CI/build/training), and collaborate with partner teams to productize across Megatron-LM, ModelOpt, and vLLM.

The Technical Program Manager will lead NPI programs, coordinating with engineering and cloud service partners to enhance infrastructure and automate workflows.

Lead technical customer engagements to design, build, and deploy GPU-accelerated AI/ML, DL, and data analytics solutions on cloud platforms. Create PoCs, run demos, collaborate with sales and engineering, deliver workshops and technical presentations, and troubleshoot customer deployments at scale.