Senior Lead Software Development Engineer Iv Android in United States

NVIDIA is looking for an experienced software engineer with infrastructure experience to become a senior member of the Cloud Foundations Automation - Development Team. We build and manage the automation ecosystem supporting NVIDIA's GPU Cloud and NVIDIA SuperPod deployments. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most hard-working and dedicated people on the planet working for us. If you're creative and autonomous, we want to hear from you! What you'll be doing: Developing software to enable efficient network design, deployment and day 2 management. Building product focused software solutions, used by internal and external customers. Helping us as we transform our workflows and organization into a centrally orchestrated configuration management framework, operating at scale across geographies. Owning and driving integrations with various service APIs such as Cloud Service Providers, to automate creation of environments and auto populate data sources in turn. Building on open source software, designing and implementing data structures and UI interfaces to automate processes from equipment purchase to device config generation to deployment to operations. Streamlining deployment mechanisms and life cycle operations Developing modern service architectures around streaming data and event pipelines. Working with infrastructure domain experts on true, zero touch deployment solutions and utilizing best of breed high performance computing management solutions. Be a proactive problem solver, looking out for new opportunities to improve our services and customer experience. Communicate readily with your peers across the organization, b

We are now looking for a Senior SRAM Engineer within our Full Custom Memory (FCM) team! The FCM team designs specialized RAM implementations across NVIDIAs wide array of processing chips. Be it high speed, low power, multiport, we engage closely with processor architecture teams to build custom solutions across the entire NVIDIA silicon portfolio. Are you interested in designing circuits for the next generation of AI chips? Join a team of dedicated engineers developing the custom SRAM circuits that help power these chips. What you'll be doing: Design best-in-class SRAM circuits using state-of-the-art technology processes Optimize circuits for performance, area, and power Collaborate with mask designers to craft high quality and dense pitch-matched layout Verify functionality, electrical integrity, and robustness Improve/develop flows and methodologies to streamline design automation, data collection, and analysis to ensure working silicon What we need to see: BS/MS/PhD (or equivalent experience) in Electrical or Computer Engineering Minimum 12 years of circuit design experience Strong understanding of SRAM and memory design techniques and macro/block development Ways to stand out from the crowd: Self-motivation, attention to detail, clear data analysis and presentation skills Familiarity with industry tools such as Cadence Virtuoso for schematic and layout, SPICE simulators, waveform viewers Background with developing and using various flows and methodologies, in

The NVIDIA DGXC Data Services team builds cloud-native systems, frameworks, and services for managing data across hybrid and multi-cloud infrastructure. We are building the next-generation data and storage infrastructure to solve some of the hardest problems in AI: storage, access, ingestion, governance, observability, and data management for exabyte-scale, high-performance GPU-based training and inference jobs. Our work gives NVIDIA teams the foundational capabilities they need to build, train, deploy, and operate AI products at scale without reinventing critical data infrastructure for every workload. What you will be doing: Build cloud-native data and storage services for hybrid and multi-cloud infrastructure, including dataset discovery, ingestion, governance, checkpointing, observability, and low-latency access. Develop scalable cloud-native services and APIs that support exabyte-scale, high-performance GPU training and inference workflows. Work closely with product managers, internal AI teams, platform teams, and partner engineering teams to understand requirements and turn them into reliable production systems. Collaborate with SRE, operations, and support teams to improve service reliability, performance, observability, on-call readiness, and operational scale. Use modern software engineering practices, including AI-assisted and agentic development workflows, while maintaining high standards for design, testing, security, and verification. What we need to see: BS in Computer Science, Information Systems, Computer Engineering, or equivalent experience, with 5+ years of software engineering experience. Strong foundation in algorithms, data structures, distributed systems, and practi

We are developing advanced multi-rack, multi-tenant AI/ML datacenters with NVIDIA GB200, and upcoming GB300 GPUs. NVIDIA seeks a Senior Software Engineer for our CSP (Cloud Service Provider) Engagements team to focus on the cloud-native stack for datacenter products like GB200. In this role, You will define customer workflows, prototype stack enhancements, and debug the toughest Kubernetes + Slurm issues in multi-rack, multi-tenant AI datacenters. You'll tackle complex scheduling challenges across racks, tenants, and clouds as part of the CSP engagements team. What you’ll be doing: Perform deep-dive debugging of multi-rack, multi-tenant clusters: scheduler behavior, container runtime issues, device-plugin crashes, RDMA/IB fabric anomalies, etc. Gather customer requirements and prototype feature extensions for Kubernetes operators, Slurm plugins, and custom micro-services that expose new GPU capabilities. Drive joint architecture reviews and “whiteboard” sessions with CSP and internal platform teams; convert findings into RFCs and upstream pull requests. Create reproducible testbeds (Helm/Ansible/Terraform) that mirror customer environments; automate validation and benchmark suites. Deliver technical collateral-design docs, how-to guides, demo scripts-and present at customer on-sites, KubeCon, and SlurmUG. Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation. What we need to see: Strong source-level expertise in Kubernetes internals (scheduler, CRI/CNI/CSI, operators) and Slurm (federation, power-save, plugins). Hands-on experience integrating next-gen GPUs (Blackwell/GB200/GB300) or comparable accelerators into containerized clusters. Proven track record debugging large-scale, cloud-native stacks across ne

NVIDIA is seeking a Senior Firmware Engineer to join our CSP Engagements team, focusing on system software for Datacenter products such as GB200. This role combines deep technical expertise in embedded firmware development with customer-facing responsibilities to enable cloud service providers with next-generation computing platforms. You will work at the intersection of hardware and software, driving technical solutions from concept through deployment. What you will be doing: Design and develop firmware solutions for manageability and observability of data center servers. Actively participate in hardware bring-up activities, OOB firmware development, protocol stacks (Redfish, PLDM, MCTP, NSM) and hardware-software co-design for Cloud Service Provider deployments. Debug and troubleshoot NVIDIA GPU firmware issues, power management, performance, and thermal control problems for data center deployments, providing active support to CSPs. Partner directly with CSPs to deliver technical solutions, co-develop & co-debug features and optimizations, and provide support during new product introductions. Perform advanced system debugging, root cause analysis, and performance optimization for large-scale data center environments. Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation. What we need to see: Deep expertise in data center server architectures, HPC systems, and hardware-software co-design. Deep expertise in embedded firmware, server management controllers, and hardware bring-up with proven track record of shipping production BMC solutions Strong knowledge of DMTF protocols (Redfish, IPMI, PLDM, MCTP, SPDM), telemetry frameworks, and out-of-band management architectures Expert-level skills in C/C&

NVIDIA is the defining technology company of the Artificial Intelligence era. Our legacy of innovation is powered by extraordinary technology—and extraordinary people. Achieving what has never been done before demands vision, innovation, and the world’s best talent! We are seeking a deeply technical Product Manager to shape the enterprise software stack for next-generation AI factories, built on NVIDIA’s industry-leading GPUs and purpose-designed CPUs. This includes bare-metal orchestration, Kubernetes-native services, and full-stack AI platform capabilities to power the enterprise AI factory. At NVIDIA, you will be part of a diverse, collaborative environment where everyone is inspired to do their best work. Join us and see how you can make a lasting impact on the world. NVIDIA’s Enterprise Product Group is a small, dynamic, and highly motivated team behind DGX systems and DGX SuperPOD—the platforms that established NVIDIA as the gold standard in AI development and deployment. By delivering turnkey, integrated solutions, the team helped transform NVIDIA from a GPU hardware vendor into a full-stack AI and data-center company. We are looking for a proven product leader with a strong track record of delivering enterprise platforms and the expertise to drive continued adoption of these solutions across global enterprises! What you'll be doing: Understand NVIDIA’s strategic position and deliver an enterprise computing platform recognized as the best in the industry. Own the complete solution lifecycle—from solution definition through development and go-to-market—for NVIDIA Mission Control software stack to drive adoption of the NVIDIA technologies in Enterprise market. Leverage strong technical background to define product requirements and user stories for solutions by channeling customer needs, solution-architecture feedback, and cross-team input within NVIDIA. Establis

We are looking for a Senior Software Engineer to become part of our storage management plane team. The management plane is a web-based application crafted to provide our storage customers the capabilities to handle and supervise our distributed storage infrastructure. Our team is continually dedicated to acquiring and implementing ground breaking technologies to overcome obstacles and innovate solutions for improving our ability to handle large clusters of machines efficiently. What You Will Be Doing: Maintain and develop Kubernetes operators and our Container Storage Interface (CSI) plugin. Develop a web-based solution that manages, operates and monitors our distributed storage. Work closely with other teams to define and implement new APIs. What We Need to See: B.Sc., M.Sc. or Ph.D. in Computer Science, or related discipline, or equivalent experience. 8+ years of experience in web development ( both client and server ) Proven experience with Kubernetes (K8s), including developing or maintaining operators and/or CSI plugins. Experience scripting with Python, Bash or similar. Experience with nodejs is a must At least 5 years of experience working in a Linux OS environment You’re smart and a quick learner You do what it takes to get the job done Passionate about coding and big challenges Ways to stand out from the crowd: NodeJS for the server side: dominant modules are async & express . Kafka, MongoDB, K8s JavaScript frameworks: React, jQuery, c3j

The NVIDIA DGXC Data Services team builds cloud-native systems, frameworks, and services for managing data across hybrid and multi-cloud infrastructure. We are building the next-generation data and storage infrastructure to solve some of the hardest problems in AI: storage, access, ingestion, governance, observability, and data management for exabyte-scale, high-performance GPU-based training and inference jobs. Our work gives NVIDIA teams the foundational capabilities they need to build, train, deploy, and operate AI products at scale without reinventing critical data infrastructure for every workload. What you will be doing: Build storage technologies, client libraries, and filesystem frameworks that help AI workloads access data across object stores, file systems, and hybrid cloud infrastructure. Develop high-performance storage paths for training and inference workflows, including data loading, checkpointing, caching, POSIX-style access, and object-store integration. Build observability systems that diagnose storage bottlenecks, attribute GPU idle time to I/O behavior, and expose actionable telemetry through production monitoring stacks. Improve performance, scalability, and reliability of storage systems serving massive datasets, deep directory trees, and high-concurrency AI workloads. Work closely with internal AI teams, platform teams, SRE, and operations to validate storage behavior against real workloads and production environments. Use modern software engineering practices, including AI-assisted and agentic development workflows, while maintaining high standards for design, testing, security, performance, and verification. What we need to see: BS in Computer Science, Information Sys

The Opportunity The world of design is changing rapidly, and the Pro Design team is leading that transformation. We are the Adobe organization behind Illustrator, InDesign, and emerging experiences that connect creativity, collaboration, and AI. Our teams are reimagining what professional design looks like for the next decade - building intelligent, connected tools that empower creators and teams to move faster without sacrificing craft. We are looking for a Senior Business Data Scientist who is creative, analytical, and unafraid to question the status quo and shape the decisions that move key business metrics at scale. Join us and build Adobe’s future products! What you'll Do Map the user funnel and build the metrics, cohorts, and dashboards that Product and Growth rely on to see how users move across free, trial, and paid tiers—and pinpoint where they drop off. Dig into the hard questions (what drives activation, which behaviors predict retention and expansion) and build propensity models for conversion, upgrade, churn, and expansion that feed real-time targeting and in-product nudges. Find and size growth bets and work with Product to ship them. Set north-star, driver, and guardrail metrics with your partners, and stand up multivariate experiments across onboarding, paywalls, in-product prompts, and pricing. What you need to succeed Minimum Requirements: Bachelor's degree in a quantitative field (Statistics, Mathematics, Computer Science, Economics, Engineering, or similar) or equivalent practical experience. 5+ years of experience in data science, product analytics, or a similar quantitative role. Proficiency in SQL and Python (or R) for data manipulation, analysis, and modeling. Hands-on experience designing and analyzing A/B tests and interpre

About Flexport: At Flexport, we believe global trade can move the human race forward. That’s why it’s our mission to make global commerce so easy there will be more of it. We’re shaping the future of a $10T industry with solutions powered by innovative technology and exceptional people. Today, companies of all sizes—from emerging brands to Fortune 500s—use Flexport technology to move more than $19B of merchandise across 112 countries a year. The recent global supply chain crisis has put Flexport center stage as we continue to play a pivotal role in how goods move around the world. We are proud to have the support of the best investors in the game who believe in our mission, solutions and people. Ready to tackle global challenges that impact business, society, and the environment? Come join us. The Opportunity: Flexport IT is looking for a Senior Systems Engineer (Identity & Access) . In this role, you will design, implement, and administer our Identity and Access Management (IAM) solutions to ensure secure, efficient user lifecycle management. While you are our resident Okta expert, you are also a high-level IT generalist. You will oversee our broader SaaS ecosystem (Google Workspace, Slack, Jira) and endpoint management infrastructure (Jamf, Intune). Your expertise will drive automation, protect sensitive data, mitigate security risks, and maintain compliance in a heavily regulated industry. You will continually strive towards automation of toil. If you are still manually doing the same operational tasks 18 months from now, something has gone wrong. Flexport’s book of business is growing fast, but the promise of technology is that we can grow our business faster than our headcount. The automation you build will be a key factor in that effort. You Will IAM Architecture: Design, implement, and maintain the end-to-end lifecycle of Identity and Access Management platforms. Okta & Directory Trust: Administer Okta, directory services, Multi-Fact

NVIDIA is leading groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU -- our invention -- serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables groundbreaking creativity and discovery, and powers inventions that were once considered science fiction, including artificial intelligence to autonomous cars. We are the GPU Communications Libraries and Networking team at NVIDIA. We build communication libraries like NCCL, NVSHMEM, and UCX that are crucial for scaling Deep Learning and HPC. We're seeking a Senior Software Architect to help co-design next-gen data center platforms and scalable communications software. DL and HPC applications have a huge compute demands and already run at scales of up to tens of thousands of GPUs. GPUs are connected with high-speed interconnects (e.g. NVLink, PCIe) within a node and with high-speed networking (e.g. InfiniBand, Ethernet) across nodes. Efficient and fast communication between GPUs directly impacts end-to-end application performance. This impact continues to grow with the increasing scale of next generation systems. This is an outstanding opportunity to advance the state-of-the-art, break performance barriers, and deliver platforms the world has never seen before. Are you ready to build the new and innovative technologies that will help realize NVIDIA's vision? What you will be doing: Investigate opportunities to improve communication performance by identifying bottlenecks in today's systems. Design and implement new communication technologies to accelerate AI and HPC workloads. Explore innovative solutions in HW and SW for our next generation platforms as part of co-design efforts involving GPU, Networking, and SW architects. Build proofs-of-concept, conduct experiments,

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. We are looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect -- for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models. Improve AI compilers to hide communications or perform automatic fusion. Conduct in-depth AI workload performance characterization on multi-GPU clusters. Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads. Author

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for phenomenal people like you to help us accelerate the next wave of artificial intelligence. We are looking for a highly motivated senior software engineer for an exciting role in our communication libraries and network software team. The position will be part of a fast-paced crew that develops and maintains software for complex heterogeneous computing systems that power disruptive products in High Performance Computing and Deep Learning. What you will be doing: Design, implement and maintain highly-optimized communication runtimes for Deep Learning frameworks (e.g. NCCL for TensorFlow/Pytorch) and HPC programming interfaces (e.g. UCX for MPI/OpenSHMEM) on GPU clusters. Participating in and contributing to parallel programming interface specifications like MPI/OpenSHMEM. Design, implement and maintain system software that enables interactions among GPUs and interactions between GPUs and other system components. Creating proof-of-concepts to evaluate and motivate extensions in programming models, new designs in runtimes and new features in hardware. What we need to see: M.S./Ph.D. degree in CS/CE or equivalent experience. 5+ years of relevant experience. Excellent C/C++ programming and debugging skills. Strong experience with Linux. Expert understanding of computer syst

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. NVIDIA has a rapidly expanding ecosystem of data center platform & node designs. From single node HGX/DGX systems all the way up to large multi-node NVLink domain rack architectures. These designs have become core to NVIDIA's rapidly growing enterprise and cloud provider businesses. Each bringing together the full power of NVIDIA GPUs, NVIDIA NVLink, NVIDIA InfiniBand networking, NVIDIA Grace CPUs, and a fully optimized NVIDIA AI and HPC software stack. We’re searching for a highly motivated, technical leader to design, drive, and operationalize rack-scale factory and deployment flows for next-generation data center products. The ideal candidate will combine deep systems expertise, decisive technical leadership, and a passion for building reliable, debuggable, and scalable manufacturing and deployment solutions. What you’ll be doing: Lead and drive rack-scale/L11 flows for factory and initial data center deployment. Design and implement end-to-end factory workflows, including firmware flashing sequences, security provisioning, and deployment of software mitigations. Collaborate with data center architects, ODMs, and OEMs to define factory and data center requirements that ensure efficient and reliable production ramp. Champion reliability, debuggability an

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. We are the GPU Communications Libraries and Networking team at NVIDIA. We deliver libraries like NCCL, NVSHMEM, UCX for Deep Learning and HPC. We are looking for a motivated Performance engineer to influence the roadmap of our communication libraries. The DL and HPC applications of today have a huge compute demand and run on scales which go up to tens of thousands of GPUs. The GPUs are connected with high-speed interconnects (eg. NVLink, PCIe) within a node and with high-speed networking (eg. Infiniband, Ethernet) across the nodes. Communication performance between the GPUs has a direct impact on the end-to-end application performance; and the stakes are even higher at huge scales! This is an outstanding opportunity for someone with HPC and performance background to advance the state of the art in this space. Are you ready for to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Conduct in-depth performance characterization and analysis on large multi-GPU and multi-node clusters. Study the interaction of our libraries with all HW (GPU, CPU, Networking) and SW components in the stack Evaluate proof-of-concepts, conduct trade-off analysis when multiple solutions are available Triage and root-cause performance issues reported by our customers Collect a lot of performance data; build tools and infrastructure to visualize and analyze the information <li