Top Tech Jobs & Startup Jobs

Develop and support software tools for chip design and verification, optimize workflows, work collaboratively to create high-performance software.

Primary point-of-contact for a customer, providing on-site and remote HPC, Ethernet, and AI infrastructure support. Troubleshoot Linux systems, networking protocols, and interoperability; reproduce and resolve complex issues; collaborate with engineering, marketing, and support; document support methodologies and improve processes.

Design and implement large-scale automated test infrastructure and orchestration for confidential computing on NVIDIA GPUs. Develop test plans, automate test execution, improve coverage, collaborate across teams, and validate CUDA/driver features in distributed, heterogeneous environments using AI-assisted tools.

Drive physical design and timing for high-frequency, low-power CPUs/GPUs/SoCs from RTL to GDS2. Perform synthesis, STA, timing constraint generation, timing convergence, placement/routing optimizations, ECO implementation, DFT closure, and cross-team methodology improvements to achieve timing and power targets.

Build and maintain a Kubernetes-native deployment and automation platform: backend microservices and APIs, GitOps pipelines, CRDs/operators in Go, multi-cloud and bare-metal automation with Terraform/Ansible/Vault, staging/prod-like environments, monitoring and SLOs, and integrations with CI/CD, observability, and automated remediation to enable zero-downtime global rollouts.

Develop silicon-accurate GPU kernel microbenchmarks, model-level performance analysis, and agentic kernel optimization to maximize LLM inference throughput and latency. Attribute bottlenecks across kernel, compiler, and runtime, produce optimization policies, and collaborate with compiler, hardware, kernel, and framework teams to deliver production-grade performance improvements.

Lead design, implementation, and automation of large-scale cloud and data center test infrastructure. Develop CI/CD pipelines, validate performance, scalability, and reliability, debug clusters (network, storage, security), manage Kubernetes and cloud environments, leverage AI tools to accelerate testing, and coordinate cross-team bring-up and issue resolution.

Drive developer enablement for CUDA-Q by creating docs, examples, tooling, MCP servers, Agent Skills, prompt templates, and benchmarks. Analyze developer and agent workflows, define documentation and agent-consumable standards, run evaluations and metrics, and translate research into practical guidance to improve developer time-to-value for quantum and GPU-accelerated applications.

Design, build, and deploy LLM-powered tools, RAG-based knowledge systems, and agentic workflows to automate SOC integration tasks. Own reliability, evaluation, and observability for AI systems and collaborate with SOCD teams to scope, validate, and measure productivity gains from deployed automation.

Design, model, analyze, and validate SoC and system architectures across datacenter, automotive, and client products. Build SOC platforms, guide modeling teams, develop tests and coverage reporting, collaborate with GPU teams and EDA partners, and align cross-site modeling efforts.