Top Tech Jobs & Startup Jobs in Boston, MA

Define the vision and roadmap for large-scale LLM memory and storage systems. Design unified memory layers across GPU, host, RDMA, SSD, and cloud tiers; integrate LLM serving engines for KV-cache offload and sharing; and develop protocols for disaggregated inference. Partner with architecture and platform teams on GPUDirect, RDMA, and NVLink optimization. Lead technical direction, mentor engineers, and represent the team in technical reviews, open source, conferences, and customer engagements.

Design and implement an LLVM-based JIT backend for NVIDIA GPUs, develop compiler passes and optimizations to meet performance and compile-time targets, collaborate with hardware and application teams to resolve issues, apply modern compiler technologies, and influence future GPU architectures.

Lead the architecture and development direction of NVIDIA ALCHEMI and related AI software for chemistry and materials science. Design developer tools, APIs, and workflows; translate advances in machine learning, generative modeling, interatomic potentials, and quantum chemistry into product capabilities; coordinate researchers, engineers, product teams, partners, and customers; and represent NVIDIA at scientific and industry events.

As a Senior Solutions Architect, you will assist customers in building solutions with NVIDIA's AI technology, focusing on Generative AI and Large Language Models while collaborating across teams for performance analysis.

Develop and optimize GPU-accelerated algorithms for quantum circuit simulations, collaborating with various teams, and leading technical efforts.

The Senior Formal Verification Engineer will verify sophisticated ASIC builds using formal methods, collaborate with architecture teams, develop verification environments, and support silicon debug.

As a Principal Software Engineer, you'll develop software systems for NVIDIA's rack-scale infrastructure, defining software architecture, collaborating across teams, mentoring engineers, and ensuring high-quality technical decisions in complex environments.

Define high-level SoC subsystem and I/O architecture for LPU products, translate product requirements into architecture and IP specifications, build and validate functional/architectural models (C++, SystemC, Python), and drive tradeoffs across performance, power, reliability, and security while coordinating with IP, firmware, software, RTL, verification, and post-silicon teams.

Lead hardware-software co-design for LLM inference: drive and document architecture, build executable C++ hardware models, optimize performance with good algorithms and parallelism, diagnose cross-team chip and subsystem issues, and automate workflows to improve efficiency.

Translate cutting-edge agent research into secure, production-grade runtime systems: prototype, benchmark, reproduce methods, build agent harnesses and evaluation/red-team workflows, secure agent toolchains, and partner across research, product, and engineering to integrate features into OpenShell.