דרושים » הנדסה » Senior AI Platform Engineer

We are seeking a Network Solution Verification Engineer to join our R&D organization, focused on validating our customer-facing networking solutions at scale using a state-of-the-art End-to-End (E2E) simulation cluster environment.

In this role, you will be a hands-on technical contributor at the intersection of networking, automation, and AI-driven validation - designing and implementing the simulation frameworks, agentic workflows, and regression pipelines that ensure our networking solutions meet the highest standards of quality and real-world applicability before reaching customers.


What you'll be doing:
Designing and implementing end-to-end validation frameworks for our customer-facing networking solutions at scale, leveraging a dedicated E2E simulation cluster environment.
Writing, maintaining, and extending automated test suites and regression pipelines for networking protocols and large-scale simulation runs, ensuring repeatable, high-confidence validation outcomes.
Performing deep regression analysis on simulation results - identifying failure trends, isolating root causes, and delivering clear, actionable findings to architecture and design teams.
Developing agentic AI flows that autonomously perform regression analysis, detect coverage gaps, generate new test cases, and implement validation code - continuously learning from simulation results and product changes to accelerate coverage without manual intervention.
Integrating validation pipelines into CI/CD workflows to enable continuous, automated regression at scale, working closely with DevOps and platform teams.
Collaborating closely with Design, Architecture, and NCS teams to understand solution requirements, translate them into simulation scenarios, and provide early-cycle quality feedback that influences product direction.
Analyzing customer-reported networking issues, mapping them to simulation coverage gaps, and building targeted test cases that prevent regression.
Continuously exploring new simulation technologies, agentic frameworks, and networking standards to evolve and improve the team's validation methodology.

We are hiring a Senior Software Engineer to join the NSV tools group. You will craft high-performing software automation systems used in NVIDIA's Data Center environments. This involves our AI cluster topology generation platform that composes, configures, and validates network infrastructure behind large-scale AI clusters. You will collaborate with NIC, OS, Switch, HCA, CPU, and GPU compute teams, along with architects, network engineers, and developers. We support data growth for the worlds biggest companies. Our worldwide engineers work in a dynamic, meaningful, and fast-paced setting. Are you ready for the challenge?

What you'll be doing:

Build and develop a full-stack automation platform (Python microservices backend, modern web frontend) used to generate, configure, and validate network topologies for AI/HPC data centers.

Implement scalable, reliable, and maintainable services and APIs that turn complex infrastructure requirements into validated, exportable network configurations.

Build and refine intuitive web interfaces that guide users through an interactive, step-by-step topology development workflow.

Collaborate closely with internal and external collaborators to understand requirements and deliver robust full-cycle solutions.

Improve stability and performance across the generation pipeline through architectural improvements and code optimizations.

Troubleshoot issues in distributed, containerized environments and contribute to system observability and reliability improvements.

Work cross-functionally with architects, DevOps engineers, product managers and collaborators to ensure high-quality releases.

Participate in code reviews, technical design discussions, and continuous improvement activities within the team.

Our Networking System Product Engineering organization is looking for a Senior Data & AI Solutions Engineer - high-agency, self-directed Data & AI Solutions Engineer to partner with engineering teams and transform data, BI, automation and agentic AI into measurable engineering productivity gains.

What youll be doing:
Work closely with engineers, managers, and cross-functional teams to understand complex engineering domains, identify bottlenecks, and build practical solutions that improve decision-making, execution speed, and operational quality.
Develop and deliver production-grade tools, automated workflows, and agentic AI solutions from concept through deployment.
Run fast, high-quality proof-of-concepts on emerging AI and agentic technologies, and productize successful ones.
Implement data flywheels that continuously improve quality through telemetry, benchmarking, automated evaluation, and structured feedback loops.
Collaborate and contribute ideas and code to Product Engineering's evolving data infrastructure.
Improve data quality, integrity, governance, metric definitions, and usability across engineering domains.
Train and enable engineers, managers, and stakeholders to use data, BI, and AI tools effectively.

Our System Product Engineering team is looking for a QA Engineer to join us and help validate the software infrastructure used by multiple teams across the organizations. This role focuses on testing internal tools, backend services, workflows, automation, and the systems that support our validation processes. You will work closely with developers, infra teams, and validation engineers to ensure that our internal software is stable, reliable, and easy to use. You will contribute to building robust test coverage, improving automation, analyzing logs and test results, and driving quality throughout the development cycle.

What youll be doing:

Plan, execute, and analyze functional, integration, and regression tests for internal infrastructure software.

Develop and maintain automated test cases and test flows.

Validate backend services, data pipelines, web tools, and internal workflows.

Investigate failures, collect logs, reproduce issues, and work with developers to identify root causes.

Review and validate new features before release, ensuring they meet quality and usability expectations.

Support CI/CD flows by monitoring automated tests and contributing to improvements.

Document test scenarios, edge cases, and validation coverage.

Provide continuous feedback to developers and infra teams to improve quality and reliability.

We are building the software foundation for the next generation of AI infrastructure. As AI workloads continue to evolve, Kubernetes and the cloud-native ecosystem must evolve with them.

Our teams mission is to make Kubernetes the best platform for AI workloads. We work upstream with the Kubernetes and CNCF communities to design new APIs, build production-grade implementations, and shape the future of cloud-native infrastructure for AI.

As a Senior Software Engineer, you'll tackle the most challenging problems at the intersection of Kubernetes, distributed systems, and AI infrastructure.


What you'll be doing:

Design, implement, and upstream new capabilities for Kubernetes and CNCF projects.

Collaborate with engineering teams across us to identify AI infrastructure challenges and solve them through upstream innovation.

Work closely with Kubernetes SIGs, Working Groups, and the broader open-source community to design and implement new capabilities.

Participate in architecture discussions, API design, technical proposals, and code reviews.

Build reliable, scalable infrastructure software for next-generation AI workloads.

Write clear technical documentation and design proposals.

We are looking for an outstanding Senior Networking Software Architect to join the NIC/DPU Software and Firmware Architecture group. In this role, you will help define the next generation of our datacenter and AI networking platforms, with focus on DPU management, QoS, performance, telemetry, and software architecture across stacks. You will work closely with hardware designers, firmware/kernel driver teams, system engineers, validation, product management and customers. The role spans early architecture definition, pre-silicon design, bring-up, and production readiness for large-scale AI and cloud datacenter deployments.

What Youll Be Doing:

Own software and system architecture for next-generation DPU management, QoS, performance, telemetry, and observability features.

Define end-to-end control and management flows across DOCA, host drivers, embedded firmware, BMC, management controllers and external management systems.

Specify telemetry and observability requirements, including counters, logs, traces, events, health monitoring, debug data, and streaming telemetry.

Define management interfaces and APIs for configuration, provisioning, lifecycle operations, diagnostics, and field serviceability.

Write clear architecture specifications, interface definitions, flow diagrams, and design documents for software, firmware, and system teams.

Partner with R&D teams to translate high-level architecture into implementable designs and guide features through development, validation, silicon bring-up, and production.

Analyze system performance bottlenecks, interoperability issues, telemetry gaps, and customer-reported issues, then feed learnings into future architecture.

Collaborate with system and cluster architects to ensure NIC/DPU features fit end-to-end AI datacenter and cloud networking designs.

We are looking for a passionate and experienced software developer to join our Chip Design Technologies group, helping to build the software infrastructure and tools that shape the future of Chip Design and Verification. This role works at the intersection of infrastructure engineering, tooling, and database ownership. Youll be responsible for the backbone systems that enable the development of our industry-leading networking chips - the highway for the AI revolution.

We're looking for a senior hands-on engineer who combines deep expertise in Python automation and CI/CD data flows with a passion for large-scale compute environments. If youre excited about optimizing critical systems, owning the health of compute farms, and driving reliability across cross-functional teams, youll feel right at home here.

What youll be doing:

Partner with Chip Design teams to solve engineering bottlenecks: Collaborate closely with Design, Verification, and Methodology teams to identify workflow pain points and deliver infrastructure solutions that directly improve chip design productivity and quality.

Build automation infrastructure: Design, build, and maintain robust Python-based automation infrastructure that orchestrates chip design flows, monitoring, and infrastructure tooling.

Drive the compute infrastructure scalability, integrity and performance

Own the platform health: Take ownership of the day-to-day health, capacity, and reliability of our compute farm and storage systems. This includes leading incident response, triage, and implementing long-term fixes to ensure high availability.

We are seeking a highly skilled Senior Performance Engineer to join our Performance and R&D organizations. In this role, you will help build and evolve systems that support performance analysis, telemetry, and optimization for large-scale GPU- and CPU-based clusters used in AI and high-performance computing environments. You will work closely with hardware, networking, firmware, and software teams to collect, analyze, and interpret performance data from live systems. This is a fast-paced R&D environment where system behavior and requirements evolve rapidly, requiring adaptable engineering solutions and strong analytical thinking.

What youll be doing:

Profile, benchmark, and analyze AI and HPC workloads on GPU and CPU clusters.

Explore performance characteristics of high-performance networking and collective communications (e.g., NCCL, RDMA, MPI, RoCE).

Identify performance bottlenecks across networking, compute, memory, and system architecture.

Develop and enhance performance analysis, benchmarking, and diagnostic tools.

Define performance test plans and establish expectations for new technologies and platforms.

Collaborate across hardware, firmware, networking, systems, and software teams to provide actionable performance insights.

Support telemetry collection and data refinement efforts to enable accurate performance analysis.

Maintain high standards for data quality, reproducibility, and traceability of performance results.

We are seeking a Senior System Management Architect to join our growing team. You will be the resident expert for system management, ensuring that AI factory management components (BMCs, MCUs, CPUs, network switches and CPLDs) operate in perfect unison. You will own the lifecycle management specifications for AI factory platforms - from factory provisioning to day-one deployment. If you enjoy studying a high-level system diagram and then immediately diving into the system-level buses and interface signals topology and the associated host management protocols modeling required to make it work, this role is for you.



What you'll be doing:

System Architecture & Flow Definition: Define and document comprehensive production, provisioning, update, recovery, and reset flows for AI factory sub-systems.
Ensure system-level architectural alignment and orchestrate seamless coordination between all the AI-Factory building blocks: GPU, DPU, CPU, Switch ASIC, NIC ASIC, BMC, and peripheral components.

Protocol Implementation & Guidance: Specify the use of standard management protocols (Red-Fish, NSM, PLDM, SPDM, MCTP, NC-SI) across sub-system interfaces to implement the management tasks.

Hardware/Software Intersect: Define system-level hardware and software behavior, including CPLD logic requirements, power-sequencing dependencies, and reset orchestration (e.g., handling PCIe PERST#, SBR, and forced resets).

Interface Management: Architect intra-board communication pathways using PCIe, I2C/I3C, USB, and SPI, ensuring robust out-of-band (OOB) and in-band management connectivity.

Cross-Functional Leadership: Collaborate with Production, Hardware and Firmware Engineering, ASIC FW/Driver teams, SW/NOS teams and QA to translate architectural specifications into implementable, testable solutions.

Technical Documentation: Author rigorous technical specifications, test plans, and architectural design documents to guide development and factory production.

We are seeking an AI Networking Architect to join the Networking Research Group. This role will help bridge the gap between emerging tasks supported by advanced technologies and the data center infrastructure that powers them. In this role, you will work at the intersection of AI applications, distributed systems, networking hardware, and software architecture.

You will join a focused team of multidisciplinary engineers driving AI workload optimization through deep application understanding, network analysis, and end-to-end systems thinking. Your insights will directly shape our products across the full stack - from applications and software libraries to hardware architecture and physical design.

What Youll Be Doing:

Model the performance of complex AI workloads to identify bottlenecks and recommend system-level optimizations.

Analyze brand-new AI models, distributed training techniques, and inference workloads to understand their infrastructure requirements.

Build Platforms, simulations and HW platforms, execute AI workloads and build analytical tools to evaluate trade-offs across compute, memory, storage, and network behavior.

Translate research insights and workload behavior into actionable software, hardware, and networking architecture requirements.

Partner with architecture, software, and product teams to influence our future networking and AI infrastructure roadmaps.

Drive architectural innovation by applying deep workload analysis to real-world advanced machine learning frameworks.