Top Tech Jobs & Startup Jobs in Boston, MA

Lead architecture, deployment, and operation of a hybrid HPC–quantum platform. Manage Linux-based GPU clusters, QPU hardware, schedulers (Slurm), networking, storage, and vendor integrations. Enable researchers by optimizing, benchmarking, and documenting hybrid workflows and supporting application performance and orchestration across classical and quantum systems.

Lead development and improvement of ASIC integration, build, simulation, CI, and debug infrastructure for high-speed IO GPU IP. Apply automation, metrics, and AI-assisted workflows to improve reliability, turnaround, and debuggability. Collaborate across design, verification, firmware, methodology, and infrastructure teams to root-cause failures and deliver durable process improvements.

Verify GPU and SoC designs by defining verification scope, developing test plans and test generators, and building verification infrastructure. Collaborate with architects, designers, and pre/post-silicon teams to validate GPU interactions, memory coherency, and micro-architecture using SV/UVM and industry tools.

Design and develop server applications for managing NVLink networks, collaborate on new features, and oversee integration testing and QA.

The role involves driving physical design and timing of high-frequency DPUs and SoCs, optimizing design constraints, and ensuring performance, power, and area targets are met through various engineering analyses and implementations.

Work with ASIC Infrastructure to enhance design productivity, deploy AI toolsets at scale, and improve CI systems while solving complex issues.

As a GPU Verification Engineer, you will verify ASIC designs of NVIDIA GPUs, define verification scope, develop test plans, and collaborate with teams.

Provide technical support to NVIDIA Enterprise customers by triaging and resolving issues, working with engineering on reproductions/logs, applying AI/ML and agentic AI to build support tools and products, documenting interactions and knowledge, and owning cases to resolution (occasional weekend/holiday support).

Provide advanced support and root-cause analysis for NVIDIA networking technologies in AI clusters. Reproduce and resolve customer issues, develop fixes and tools, analyze performance/tuning for high-performance lossless networks, collaborate with R&D and customers, and occasionally support outside regular hours.

Provide advanced technical support for NVIDIA InfiniBand, NVLink and GPU-based HPC/AI infrastructure. Troubleshoot installations, networking and interoperability issues on multi-distro Linux, reproduce and resolve customer problems, use packet analysis and cluster tools, and collaborate with engineering, marketing, and support teams to improve processes and documentation.