Top Tech Jobs & Startup Jobs

Leads hardware security architecture and long-term security roadmaps for NVIDIA SoCs and GPUs. Designs mitigations for physical attacks, develops threat models for advanced packaging and photonics, reviews architecture and verification specifications, and evaluates AI-assisted vulnerability discovery. Collaborates with internal teams, customers, partners, standards bodies, and industry organizations to address security risks, supply-chain threats, hardware Trojans, fault injection, and side-channel attacks.

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.

Lead NVIDIA’s agentic developer platform strategy and execution. Build scalable platform capabilities from emerging agent patterns, including RAG, vector databases, evaluation systems, governance, safety tooling, and GPU-optimized workflows. Integrate the AI Data Platform with NVIDIA’s on-prem AI Factory, improve distributed inference performance, and establish controls for data lineage, compliance, and Responsible AI. Grow a high-performing engineering team and drive adoption of reusable APIs, SDKs, components, and reference implementations across the company.

Leads software engineering teams delivering rack-scale infrastructure software, including control planes, lifecycle orchestration, system health, recovery, and fleet-scale reliability. Owns planning, staffing, releases, quality, production support, open-source delivery, and cross-functional coordination across hardware, firmware, networking, security, operations, customers, and partners. Builds technical leadership, manages engineering performance, and guides architecture and software quality.

Develop and deploy embedded firmware for NVIDIA data center systems, including BMC solutions, hardware bring-up, manageability, observability, and out-of-band protocols. Diagnose GPU firmware, power, performance, thermal, and reliability issues; optimize large-scale deployments; and collaborate directly with cloud service providers on co-development, debugging, product introductions, and technical documentation.

Design and develop secure, scalable Salesforce AI solutions, including Agentforce agents, multi-agent orchestration frameworks, custom MCP servers, and AI-client integrations. Build integrations using APIs and platform events, implement observability and security controls, translate business requirements into technical specifications, and support AI platform users. The role requires extensive Salesforce ecosystem experience, expertise with Data 360 and Headless 360, and hands-on Python or JavaScript development for AI and MCP services.

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.

Develop and implement core firmware features for Mellanox NICs supporting cloud, HPC, and storage networking. Collaborate with architecture and software teams, create verification tests, debug complex hardware/software systems, and contribute to firmware maintenance, qualification, and releases. The role requires strong C/C++ development, networking knowledge, PCIe and virtualization experience, scripting skills, and familiarity with distributed, high-performance computing environments.

Develop autonomous driving algorithms that fuse perception and map data into real-time 3D world models. Build BEV models, occupancy grids, obstacle representations, and occlusion masks for navigation and planning. Collaborate with perception and planning teams, lead technical initiatives, ensure safety and reliability across large datasets, and recruit, mentor, and grow engineering talent. Apply expertise in computer vision, 3D geometry, sensor calibration, and state estimation to support mapless driving.

Develop and support high-performance infrastructure tools for chip design and verification. Build scalable backend and frontend web applications using Golang, TypeScript, and JavaScript; manage hardware-level product definitions; improve workflows for architecture, hardware, and software teams; and research solutions that increase engineering efficiency.