Top Tech Jobs & Startup Jobs in Boston, MA

Build and operate security controls, telemetry, detections, and enforcement for NVIDIA’s large-scale EDA compute, storage, and networking infrastructure across on-premises and multi-cloud environments. Investigate threats, respond to incidents, automate secure configurations and compliance evidence, threat-model infrastructure, and manage security technology lifecycles. The role requires hands-on Linux, networking, programming, infrastructure security, and collaboration with infrastructure and security teams.

Builds secure AI and agentic cybersecurity tooling, transforming research prototypes into production-ready services. Responsibilities include developing backend services, APIs, CLI tools, automation, and integration patterns; defining MVPs for ambiguous security and identity challenges; collaborating across research, product, enterprise security, and platform teams; and applying offensive security and adversarial thinking to address AI-specific risks such as injection, tool misuse, unauthorized access, data exfiltration, and unsafe delegation.

Conduct novel research in AI security and cybersecurity, focusing on securing AI models, agents, systems, and infrastructure. Develop tools and processes to identify and remediate vulnerabilities, investigate adversarial machine learning, publish findings, and collaborate across NVIDIA. Present complex technical results to security, machine learning, and business audiences while contributing to secure software development and AI safety.

Develop and maintain automated integration and deployment for components in a Kubernetes-based software stack. Manage third-party dependencies, validate compatibility, maintain integration workflows, troubleshoot cross-component issues, and ensure compatibility with NVIDIA hardware. The role requires extensive Linux software development experience, Python proficiency, Kubernetes and container expertise, and collaboration with QA, CI/CD, development teams, and upstream projects.

Lead the architecture and implementation of NVIDIA’s large-scale data retrieval platform for foundation-model training. Build web crawling, source discovery, indexing, scheduling, fetching, ingestion, provenance, and policy-enforcement systems. Ensure production reliability, scalability, observability, and cost efficiency while supporting open-web, licensed, partner, code, STEM, and multimodal data. Partner across engineering, research, product, legal, privacy, and governance teams, mentor engineers, and set technical direction.

Design, implement, and optimize scalable high-performance dense linear algebra kernels for GPUs. Provide technical leadership, collaborate with product and partners, improve performance and quality, and contribute to library roadmaps and development practices.

The Senior HPC Architect role involves deploying large-scale GPU compute clusters, optimizing system administration, and collaborating with researchers on HPC and AI solutions.

Develop and optimize GPU-accelerated numerical linear algebra libraries for AI and high-performance computing. Design kernel generation, JIT compilation, matrix operations, and operator fusions; lead projects involving multiple engineers and teams; provide technical mentorship; collaborate with product management and customers on requirements and roadmaps; and improve performance and maintainability through architectural enhancements.

Lead the technical direction and development of NVIDIA Dynamo, an open-source, production-scale AI inference platform. Drive initiatives in resilience, performance, scalability, and inference infrastructure while collaborating across storage, networking, hardware, and performance teams. Represent Dynamo with customers and the AI community, guide technical strategy, and promote emerging AI/ML infrastructure technologies. The role requires deep systems software, production inference, and senior technical leadership experience.

Lead technology strategy and system architecture for next-generation wireless infrastructure. Apply AI/ML to RAN (L1/L2+) and transform core to agentic AI-based packet core. Prototype GPU-accelerated algorithms, engage partners and standards bodies, and drive performance optimizations and new edge applications (ISAC, SemCom, Physical AI).