Top Tech Jobs & Startup Jobs in Boston, MA

As a System Software Engineer at NVIDIA, you'll develop GPU architecture, improve performance testing, and enhance workflows for chip designers, working closely with both software drivers and GPU simulations.

The role involves developing system software for NVIDIA's DPU, including firmware and drivers, collaborating with hardware teams, and tackling system-level optimizations.

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

Verify ASIC designs and high-speed I/O controllers at IP, subsystem, and SoC levels using UVM and coverage-driven methodologies. Develop reusable models, monitors, checkers, scoreboards, test plans, tests, and verification infrastructure. Perform random-stimulus, functional-coverage, assertion-based verification and debugging while collaborating with architects, designers, and pre- and post-silicon teams. Relevant protocols include Ethernet, NVLink, USB, SATA, and CXL.

Lead development and validation of LLM inference platforms for NVIDIA edge GPUs. Track open-source framework innovations, analyze model-to-hardware mapping, optimize GPU kernels and multi-node inference, produce performance reports, maintain developer inference recipes, own model bring-up workflows, and support partners on hardware-specific inference issues.

The role involves researching and developing GPU-accelerated AI workloads, optimizing algorithms, and collaborating with technical experts to improve hardware performance.

Lead a team to optimize algorithms for Deep Learning and Machine Learning, define technical initiatives, and collaborate with various teams for hardware and software innovation.

The role focuses on optimizing and managing workload scheduling systems for EDA, enhancing observability, service reliability, and automation while resolving performance issues.

The Senior Software Architect will design and implement communication technologies, improve performance for AI and HPC workloads, and lead innovative GPU communication solutions.

You will integrate communication libraries into AI frameworks, analyze workloads, improve AI compilers, and author custom kernels for performance.