Jobs at NVIDIA

Lead development and adoption of AI-driven architecture workflows for NIC and switch platforms. Define roadmap, build agentic flows with AI engineering, validate architecture outputs, collaborate with architects and leadership, run betas, and drive organization-wide tooling adoption to shorten design cycles and raise output quality.

Leads technical Developer Relations for NVIDIA AI platforms across India's financial services AI labs. Builds adoption strategies, technical demos, benchmarks, reference architectures, workshops, and performance guides. Works directly with researchers, infrastructure teams, and CTOs to profile workloads, optimize inference, debug integrations, and design secure, observable GPU deployments across cloud, data centers, Kubernetes, and hybrid environments. Translates developer feedback and workload requirements into product and engineering input.

Designs and verifies physical layouts for silicon interposers used in NVIDIA GPU and SoC packages. Collaborates with package, signal integrity, technology, and design teams to evaluate feasibility, optimize floorplans, resolve manufacturing and electrical issues, and deliver layouts on schedule. Uses Cadence tools for custom layout, design-rule and netlist verification, and recommends layout trade-offs involving size, cost, and system performance.

Architect and implement OpenBMC-based management for server platforms integrating BMCs, host CPUs, and top-of-rack Ethernet switches. Develop D-Bus services, Redfish APIs, object models, telemetry, security, firmware, and L2 networking capabilities. Build backend abstractions supporting switchdev, SAI, SONiC, DENT, and vendor SDKs. Collaborate across hardware, security, firmware, QA, manufacturing, and networking teams to deliver reusable, testable platform-management architecture.

Design and validate end-to-end AI and HPC infrastructure solutions involving GPU servers, storage, and SONiC-based networking fabrics. Lead customer-facing technical evaluations, demonstrations, proofs of concept, benchmarking, and production support. Configure and troubleshoot networking, firmware, drivers, operating systems, routing, and GPU performance. Manage customized SONiC projects and collaborate with engineering, product, account, and OEM partner teams to resolve complex infrastructure issues.

Develop and optimize GPU-accelerated parallel algorithms and data structures for application developers. Collaborate with NVIDIA architecture, research, libraries, tools, and system software teams to influence next-generation architectures, software platforms, and programming models. Apply software design, algorithms, mathematical fundamentals, linear algebra, and numerical methods to improve application performance and developer efficiency. Travel occasionally for conferences and on-site developer visits.

Architect ASIC system requirements for high-speed networking systems, focusing on yield, performance, reliability, and manufacturing quality. Collaborate with architecture, logic design, software, firmware, and hardware teams to integrate complex system components. Lead implementation and project execution against ambitious deadlines and performance targets for InfiniBand, NVLink, and Ethernet switching products used in advanced computing clusters.

Leads NVIDIA BlueField DPU and DOCA networking solutions for major Chinese cloud service providers. Designs North-South network architectures, API Gateway acceleration, traffic orchestration, telemetry, inference networking, and dataplane optimizations for Agentic AI workloads. Partners with sales, customers, and global engineering teams; leads workshops, proofs of concept, pilots, deployments, open-source contributions, and technical roadmap development. Mentors solution architect teams and delivers measurable latency, throughput, and total-cost improvements.

Build scalable infrastructure for large-scale AI architecture simulation studies across on-premises clusters and cloud environments. Develop distributed execution, unified storage, data platforms, automation, and visualization tools for reliable, reproducible analysis. Partner with GPU architects, performance engineers, AI researchers, and software teams to support emerging AI workloads, improve system efficiency, and define the technical roadmap for next-generation simulation platforms.

As a design team lead at NVIDIA, you will manage and mentor a team contributing to SONiC software development while collaborating on features in a fast-paced environment.

Verify ARM architecture-based CPU cores by developing unit-level verification plans, testbench components, and stimulus using RIS tools. Collaborate with design and architecture teams to validate architectural and microarchitectural features, analyze verification strategies, and incorporate AI-accelerated workflows. The role requires CPU verification experience, ARM architecture knowledge, strong verification methodology skills, and detailed problem-solving abilities.

Design and improve security architecture for NVIDIA networking firmware and embedded subsystems. Responsibilities include threat modeling, identifying firmware and hardware interaction weaknesses, defining lifecycle security features, translating threats into requirements, partnering on hardware security primitives, and guiding secure firmware development. The role covers secure boot, identity and key storage, privilege separation, attestation, debug authorization, secure updates, memory-safe C practices, static analysis, and fuzzing.

Own NVIDIA’s config-as-code foundation for its EDA compute farm. Design LSF deployment schemas, build federated deployment pipelines with staged rollout and rollback, eliminate configuration drift, and create regression testing for scheduled LSF upgrades. Partner with an LSF specialist to encode scheduler expertise into templates and policies. The role also requires infrastructure automation, GitOps at scale, tooling development in Go, Python, and shell, and management of stateful production infrastructure.

Develop compiler verification software and infrastructure for deep learning compilers. Analyze graph transformations, IR lowering, fusion, mixed-precision optimizations, and GPU execution for semantic and numerical correctness. Build test-generation systems across model topologies, precision modes, and hardware targets, while improving functional quality and performance measurement. Collaborate with compiler and architecture teams to investigate correctness issues and edge-case failures.

Build and deploy AI/ML tools for GeForce NOW SRE operations, transforming production data, metrics, logs, and signals into incident root-cause analysis and operational forecasts. Lead LLM- and agent-based systems, develop large-scale data pipelines, optimize LLM workflows, and recommend sustainable AI platforms and architectures. The role also involves automation, Kubernetes, AWS cloud environments, monitoring, visualization, and production SRE practices.

Own NVIDIA’s marketing engagement across open source foundations and developer communities, anchored by PyTorch. Drive technical content, conference presence, foundation committee participation, stakeholder alignment, budgets, and community relationships. Use AI agents, automation, and dashboards to improve monitoring, planning, reporting, and program execution. The role requires strong developer marketing judgment, technical fluency in AI or scientific computing, and experience managing multiple concurrent ecosystem programs.

Design and scale Kubernetes-native, GPU-accelerated cloud architectures for large-scale robotics simulation, synthetic data pipelines, training, and inference. Advise partners, optimize scheduling, storage, networking, and GPU utilization, and drive adoption of NVIDIA Physical AI frameworks while collaborating with product and engineering teams.

Lead HBM and LPDDR system integration and bringup for next-generation SoCs. Own memory performance, power, thermal, and reliability closure across silicon, package, board, and firmware. Drive post-silicon margining, VF shmoo, eye characterization, and correlation. Debug training, calibration, SI/PI, and system stability issues. Define validation, characterization, and issue-tracking plans to produce production-ready operating points.

Own and grow relationships with leading game studios, manage technical and commercial partnerships end-to-end, drive integrations of NVIDIA gaming technologies, negotiate and close deals, advocate partner needs to product teams, and coordinate go-to-market and marketing initiatives.

Develop trusted firmware and low-level system software for NVIDIA Tegra platforms using ARM technologies. Responsibilities include early boot, EL3 services, power management, operating system and hypervisor interfaces, AI-assisted engineering workflows, debugging, validation, security, architectural analysis, and upstream contributions involving Confidential Compute, PSCI, FFA, and RMI.