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We are now looking for a Senior Deep Learning Software Engineer, PyTorch. NVIDIA is hiring software engineers to design and build tools used by AI engineers across the world to design, develop, and deploy AI applications scalable across thousands of GPUs. This position will embed you in an ambitious and diverse team that influences all areas of NVIDIA's AI platform as well as directly contributes to PyTorch, a premiere deep learning framework. In this role you will work with multiple teams at NVIDIA across fields, as well as collaborate internationally with the PyTorch community to develop the best AI platform in the world. What you will be doing: Design and build PyTorch components that run efficiently on supercomputers with 1000s-100ks of GPUs. Collaborate with NVIDIA’s hardware and software teams to improve the overall GPU performance in PyTorch. Design, build and support production AI solutions used by enterprise customers and partners. Work with internal applied researchers to improve their AI tools. What we need to see: BS in Computer Science or Engineering (or equivalent experience). 3+ years professional experience in deep learning. Proficient with C++ programming. Strong understanding of systems software and interfaces. Demonstrated experience with Thread and Distributed Parallel Programming Demonstrated background developing large software projects. Strong verbal and written communication skills Ways to stand out from the crowd: Contributions and participation in the open source community. Familiarity with deep learning compilers. Familiarity with deep learning modeling trends. Background with CUDA Programming as well as Python.

Distributed Systems engineers at Datadog design, implement and run in production the foundational platforms powering our applications. Your data pipelines will ingest, store, analyze and query in real-time billions of events per second from companies all over the globe. The platforms are optimized for durability, high availability, low latency, internet-scale footprint and operability. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Build fault-tolerant, horizontally scalable solutions running in multi-tenant environments Write in Go, Java Rust or C++, amongst other languages Use Kafka, Redis, Cassandra, Elasticsearch and other open-source components Own meaningful parts of our service, have an impact, grow with the company Who You Are: 6+ years of experience You have a BS/MS/PhD in a scientific field or equivalent experience You have significant backend programming experience in one or more languages (Go, Java, Rust, C++) You have been exposed to working on problems (high durability / low latency /…) You can get down to the low-level when needed You care about simple designs and performance You want to work in a fast, high-growth startup environment that respects its engineers and customers You have demonstrated ability to use AI coding tools in day-to-day workflows and validate, critique, and refine AI-generated output. Bonus: you’re motivated to push the boundaries of how AI can improve software engineering best practices and contribute to building AI-enabled products. This job is available in various departments within our company; to conform to US export control regulations, some of these roles may require candidates to be eligible for any required authorizations from the US government. Datadog values peo

NVIDIA is a global leader in high-speed computer vision, artificial intelligence (AI), and deep learning. Our team develops data engineering solutions that empower AI developers in autonomous vehicle (AV) domains to innovate quickly and effectively at scale. Are you ready to take on a senior technical role in building high-performance AI data pipelines? We seek an exceptional individual to design and optimize microservices and data pipelines to process massive volumes of AV data and enable seamless data mining and AI training. The ideal candidate will bring expertise in big data processing and distributed computing to create efficient solutions and overarching architectures for challenges such as video data curation, behavioral search, and AI dataset management. What you'll be doing: Scope and build tools, microservices, workflows, and distributed applications to accelerate data mining and AI training. Design and implement solutions for streaming, resilience, logging, security, authentication, workflow orchestration, and data management. Deploy AI models. Design and develop Retrieval-Augmented Generation (RAG) workflows enabling hybrid and agentic patterns. Analyze and operationalize complex distributed systems for speed-of-light performance. What we need to see: Experience developing high-performance, scalable software systems. MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field. Strong programming skills in Python or Golang Proficiency in key technologies like Kubernetes, Helm, Hive, Parquet, SQL, vector databases, e.g., Milvus. Strong architectural skills with a proactive, problem-solving mentality. Experience in data mi

NVIDIA Architecture Modeling group is looking for Architects, Functional Modeling Engineers, and Simulation experts to join various architecture efforts across GPU/ SOC Architecture teams. A key part of NVIDIA's strength is to innovate in parallel computing fields, delivering the highest performance in the world for high-performance computing. We are constantly looking for ways to improve our SoC and Systems architecture and maintain our leadership. In this position, you will be working with other world-class architects on modeling, analysis and validation of chip & system architectures and features that advance the state of art in performance and efficiency. What you'll be doing: Modeling and analysis of SoC & Systems algorithms and features, across datacenter, automotive, and client products Build and deliver platforms for SOC's that enable left shift for the SW teams aligned with project milestones Work closely with the SOC architects and guide modeling teams to deliver high-quality functional models that involve SOC+GPU use cases Collaborate with our EDA partners to align on customer-facing technologies Develop tests, test plans, and testing infrastructure for new architectures/features and code coverage analysis and reporting Ensure alignment between the various modeling teams at NVIDIA, GPU modeling teams, and modeling teams overseas What we need to see: Master’s or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related relevant field (or equivalent experience) with 5+ years of relevant work experience. Strong programming ability: C++, C along with a good understanding of build systems (CMAKE, make) , toolchains (GCC, MSVC) and libraries (STL, BOOST) Computer Architecture background with experience in modelling wit

The DFP Engineer – Manufacturing role defines and implements the validation and screening of new silicon features within high‑volume manufacturing flows. You will translate product requirements into executable test methodologies, infrastructure, and detailed manufacturing test plans that ensure quality, yield, and efficiency at scale. This role sits at the intersection of multiple multi-functional teams to make manufacturing test an outstanding part of the overall codesign and DFP lifecycle. What you will be doing: Own end-to-end manufacturing test methodology across all test stages. Translate system specs and product POR into DFP requirements, test content, coverage, and flows. Define and maintain the DFP roadmap, including infrastructure and turning point planning. Partner multi-functionally to implement test content, debug hooks, and coverage improvements. Drive alignment on manufacturability, test time, binning strategies, and cost vs. coverage trade-offs. Embed testability requirements into design to enable robust screening and debug. Define data and analytics frameworks to support yield analysis and continuous improvement. Lead DFP documentation as the single source of truth and feed findings into future methodologies. What we need to see: MS in Electrical Engineering, Computer Engineering, or related field (or equivalent experience) 6&#43; years in silicon post‑silicon validation and/or high‑volume manufacturing test for complex SoCs, GPUs, CPUs, or similar. Hands‑on experience with test content bring‑up, limit setting, correlation to characterization, and yield/coverage optimization. Proficiency with scripting and data analysis (e.g., Python, MATLAB, R, SQL) for test data analytics, limit tuning, and yield/debug analysis. <

NVIDIA's GPUs and SOCs are the world leaders in power, performance and efficiency. We are continually innovating to deliver new and creative, unusual solutions to extraordinary problems in a wide range of sectors. To this purpose, we are now seeking a hard-working Senior Package Layout Engineer who is committed to making a difference in the world through their contributions! This position will collaborate with Technical Package Lead and different design teams in the design and development of sophisticated, detailed layout of IC substrates for NVIDIA products. In addition, work with design teams to plan schedules, resolve costs, manufacturing, and electrical design issues. What you'll be doing: As part of a Layout team, you will collaborate to implement high speed/density ASIC packages. Perform substrate breakout patterns for ASIC packages. Optimize package pinout incorporating system level trade-offs of pins assignment. Help perform package routing, placement, stack-up, reference plane and power distribution using Cadence APD or SiP tool suite. Propose layout design trade-offs to the Technical Package Lead for resolution and implementation. Conduct design feasibility studies to evaluate the Package design goals for size, cost, and system performance. Develop symbols and CAD library databases using Cadence APD design tools Develop methodologies to improve layout productivity What we need to see: Hold a B.S. Electrical Engineering or equivalent experience 5&#43; years experience in PCB Layout of graphics cards, motherboards, line cards or other related technology. Experience with HDI designs is a plus Proven experience in substrate layout of wire bond and flip chip packages, preferred Significant background with Cadence AP

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. Come join the team and see how you can make a lasting impact on the world. At NVIDIA, we are seeking a Senior Account Manager who will bring technical and business insight to help grow the Networking business with Cloud Service Providers, leveraging NVIDIA’s fast-growing Datacenter Networking Business. What you'll be doing: You will be an integral part of a small, forward-thinking team responsible for a significant and rapidly growing revenue contribution to the Enterprise products group, the fastest growing and most dynamic segment at NVIDIA. Working with leading CSP to grow deployment of NVIDIA networking solutions Define and drive the discussions, strategy and tactics for achieving revenue growth Partner and collaborate with technical teams on roadmap updates, new designs, competition Representing the customer’s strategy & needs to internal stakeholders and vice versa Delivering a concise state of the business at any given time What we need to see: Bachelor’s degree or higher in related field (or equivalent experience). 12&#43; years of Technical Sales or Product Management with focus on Data Center Networking for CSPs An understanding of the business and technology landscape of CSP Data Center Networking <l

NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company”. We are looking to grow our company, and grow our teams with the smartest people in the world. What you’ll be doing: You will work with ground breaking technologies for the Tegra SoC and various NVIDIA embedded platforms Implement power and thermal management software features in Linux Kernel and user space Collaborate with power architects, hardware and software engineers on platform power estimation and optimization Optimize the software stack to improve performance, efficiency, and responsiveness for edge AI and robotics use cases. Focus on improving compute and memory utilization, reducing latency and power consumption, and tuning system-level performance to deliver reliable and scalable AI workloads across demanding real-world edge environments. What we need to see: MS in CS, CE, EE, Systems Engineering or related software/hardware engineering major, or equivalent experience 8&#43; years of software development experience with a significant focus on Linux Excellent C programming/debugging skills within Linux kernel and user space software Background with working on embedded systems and ARM processor specific System-level debugging experience and problem-solving skills Excellent communication skills Ways to stand out from the crowd: Understanding of the Linux power and thermal management features (schedule

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Senior Principal Network Engineer to help design, deploy, and optimize next‑generation AI data center networks. AI training and inference workloads require extremely high bandwidth, deterministic low latency, and zero‑packet‑loss networking environments. In this role, you will partner closely with the Network Architecture Lead to design and scale high‑performance computing (HPC) network fabrics supporting GPU clusters. You will work across hardware, networking, and AI application layers to ensure Graphcore’s large‑scale AI infrastructure operates at peak performance. The ideal candidate brings deep experience operating hyperscale or HPC data center networks and has expertise in high‑speed Ethernet fabrics, RDMA technologies, advanced automation, and telemetry systems. The Team The Data Center Network Engineering team designs and operates the high‑performance network fabrics that power Graphcore’s AI compute platforms. The team collaborates closely with hardware engineering, AI researchers, and infrastructure teams to build scalable networking environments optimized for distributed training and infe

The Applied AI team designs and builds algorithmically driven features in the Datadog app. We work across a range of applications, primarily focusing on analysis on streaming data such as anomaly detection, error outliers and faulty deployment analysis. As an Applied Scientist you will work on building models and algorithms for machine learning powered features within the Datadog platform. You will work closely with our engineering and product partners to explore, build, scale and deliver these features that we incubate within the Applied AI team. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Design solutions for our different use cases. You will research and benchmark relevant algorithms to find the best fit for our use-cases Leverage machine learning algorithms and statistical techniques to build new scalable product features Develop, deploy and monitor new and existing features to production Participate in our journal club by reading and presenting the latest academic research papers to the team Explore, analyze and tell the story behind high volumes of data flowing through Datadog systems Maintain and monitor the models, services and infrastructure owned by your team Participate in your team’s on-call rotation Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering, Machine Learning or related scientific field or equivalent experience You have experience working with high-scale systems and datasets including building models, applying machine learning to real business problems, and writing production data pipelines You can explain complex ideas and algorithms to non-technical audiences You care about code simplicity and performa

We are looking for a Senior System Software Engineer, Software Defined Networking to design, build, and operate highly performant and scalable SDN solutions for NVIDIA's AI Clouds hosting GPU-accelerated workloads — including hyperscale multi-node training, inference, cloud gaming, and cloud functions. This role spans the full lifecycle of our SDN stack — from designing and developing new control and data plane software to ensuring operational excellence in production through reliability engineering, CI/CD, observability, and incident response. What you'll be doing: Design and develop next-generation multi-tenant cloud SDN control and data plane software (OVS, OVN, OpenFlow) Build Infrastructure-as-a-Service virtual network orchestration and services using gRPC and REST to support tenant workload security and performance SLAs for BMaaS, VMaaS, and Kubernetes Drive upstream contributions to OVN-Kubernetes and related open-source projects Develop software for network observability — monitoring, telemetry, intelligent metering, and performance analysis Operate and support OVS-OVN based SDN solutions in large-scale NVIDIA AI Cloud environments Own end-to-end observability for the SDN stack — build and maintain monitoring, alerting, distributed tracing, and dashboarding to ensure real-time insight into network health, performance, and tenant SLAs Design, enhance, and maintain CI/CD pipelines (GitLab) across Linux host networking, OVS, OVN, and Kubernetes CNIs Implement GitOps approaches or related experience for secure, seamless integration with cloud infrastructure Drive reliability through incident management, resource monitoring, and performance tuning<

NVIDIA is seeking a Senior Software Engineer to help us develop distributed storage services for AI/ML. In this role you will work closely with the broader NVIDIA team to design and build a reliable, scalable, and efficient storage-as-a-service tailored to AI applications that can be deployed anywhere and scale without limitations. This service supports the whole NVIDIA critical business from graphics drivers to autonomous vehicles to deep learning frameworks. To achieve this goal, we are looking for an engineer with a deep understanding of distributed systems, outstanding design skills, and a track record in building and delivering large-scale distributed services. What you will be doing: Leading the overall architecture and design of our distributed storage service optimized for AI/ML Develop and maintain distributed, robust and scalable Go programs deployed to state of the art open-source ecosystems, including Kubernetes. Develop and maintain user-space applications, containers, Go-bindings, and CLI tools. Building features for a distributed storage service to enhance availability and reliability for large-scale deployments Engaging and collaborating with NVIDIA Research, Computing, Product teams, cross-functional teams, and external customers to deliver Cloud services. Automating distributed storage service end-to-end, including deployment, management, and monitoring What we need to see: Bachelor’s of Science in Computer Science, or related field (or equivalent experience) with 8&#43; years of industry experience Strong background in developing distributed systems involving Golang, Kubernetes, and Cloud Service Provider integrations Strong track record of delivering distributed services in a variety of distributed computing environments Experience in i

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 the 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 a Developer Technology Engineer you will be at the forefront of innovation, working with leading industry partners and exciting OSS projects to accelerate RTX & DGX SoC performance for agentic use. This role offers an outstanding opportunity to collaborate with world-class talent and make a significant contribution to the next era of enterprise and consumer AI. What you'll be doing: Own key engagements with our fast-paced developer ecosystem partners, optimizing their applications to deliver outstanding end-to-end performance on RTX and DGX SoCs. Take ownership of performance optimization for compute-intensive CPU, AI, and 3D graphics workloads, working with domain experts to identify bottlenecks and implement effective solutions. Work across system software, GPU driver, architecture, and NVIDIA Research teams to influence next-generation, high-performance SoC platforms by bringing real-world workflows and actionable insights from partner and customer needs. Provide technical guidance and mentorship to junior engineers while contributing to an inclusive and high-performing team environment. What we need to see: BS or MS degree in Computer Science, Engineering, Mathematics or related degree (or equivalent experience) 5&#43; years of respective work experience as software developer Proficiency in C/C&#43;&#43;, Python, software

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&#43; years of software engineering experience. Strong foundation in algorithms, data structures, distributed systems, and practi