Servers Jobs

1418 Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. 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. We are opening a new AI Engineering Campus in Austin, which will play a central role in Graphcore's work building the future of AI computing. The Electrical Engineer will play a pivotal role in designing innovative hardware systems for AI/ML applications. We are seeking a motivated Electrical Engineer with 2–4 years of experience in schematic capture, PCB design, and server hardware development. This role includes close collaboration with multiple partners to drive designs from concept through mass production. The ideal candidate is comfortable working across organizational boundaries, ensuring design quality, manufacturability, and on-time delivery in a fast-paced environment. Responsibilities: Develop and maintain electrical schematics for various printed circuit assemblies Design and layout multilayer PCBs Work closely with partners to review designs, provide technical guidance, and ensure alignment with system requirements Drive design for manufacturability (DFM), design for assembly (DFA), and design for testability (DFT) Support server subsystem integration Participate in design reviews Support prototype builds, board bring-up, debugging, and validation Track and resolve design issues, including root cause analysis and corrective actions Ensure proper documentation, revision control, and engineering change management (ECO/ECN processes) Requirements: Bachelor’s degree in electrical engineering 2–4 years of experience in schematic capture and PCB design

Manufacturing Test Engineering Manager Position Summary We are seeking an experienced Manufacturing Test Engineering Manager to lead the development and execution of the end-to-end manufacturing test strategy for next-generation AI server platforms and datacenter infrastructure. This role is responsible for defining and driving the manufacturing test architecture from L6 board assembly through L11 rack-level integration and final system validation , ensuring world-class product quality, manufacturability, and production scalability. This leader will manage a team of 3–5 Manufacturing Test Engineers while partnering closely with Hardware, Firmware, Platform, Validation, Quality, Operations, and Joint Design Manufacturing (JDM) partners. The role owns the manufacturing test strategy, test coverage, factory test infrastructure, manufacturing capacity planning, and continuous improvement of manufacturing quality. Key Responsibilities Manufacturing Test Strategy Define and own the end-to-end manufacturing test strategy from L6 board assembly through L11 rack integration . Develop standardized manufacturing test methodologies that optimize quality, throughput, cost of test, and scalability across multiple products and JDM sites. Establish manufacturing test standards, best practices, and engineering processes that support high-volume server manufacturing. Technical Leadership & People Management Lead, mentor, and develop a team of 3–5 Manufacturing Test Engineers supporting multiple hardware programs. Establish team priorities, allocate resources, and ensure successful execution of manufacturing test deliverables. Foster a culture of technical excellence, accountability, collaboration, and continuous improvement. Serve as the primary technical escalation point for manufacturing test and production issues. Cross-Functional Engineering Collaboration Partner with Hardware, Platform, Firmware, Validation, Reliability, Quality, and Operations teams to ensure manufac

About the Team Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and fi nancial reporting. Team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Sta ff Software Engineer,Data to be a technical lead and help architect and scale our data reliability, data infrastructure, automation and tools to meet growing business needs. You’re excited about this opportunity because you will... Own critical data systems that support multiple products/teams Develop, implement and enforce best practices for data infrastructure and automation Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Improve the reliability and scalability of our Ingestion, data processing, ETLs, Reporting tools and data ecosystem services Manage a portfolio of data products that deliver high-quality, trustworthy data Help onboard and support other engineers as they join the team We’re excited about you because... 8+ years of professional experience as a hands-on engineer and technical leader leading multiple projects 6+ years experience working in data platform and data engineering or a similar role You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Pro fi ciency in programming languages such as Python/Kotlin/Scala 4+ years of experience in ETL orchestration and work fl ow management tools like Air fl ow Expert in database fundamentals, SQL, data reliability practices and distributed computing 4+ years of experience with the Distributed data/similar ecosystem (Spark, Presto) and streaming technologies such as Kaa/Flink/Spark Streaming Excellent communication skills and experience working

Overview: Guidepoint seeks an experienced Data/AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The Senior AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization

Overview: Guidepoint seeks an experienced AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization in production

MongoDB Technical Services Engineers use their exceptional problem solving and customer service skills, along with their deep technical experience, to advise customers and to solve their complex MongoDB problems. Technical Service Engineers are experts in the entire MongoDB ecosystem - database server, drivers, cloud, and infrastructure. This also includes services such as Atlas (database as a service), or Cloud Manager (which helps customers with automation, backup and monitoring of their MongoDB systems). Our engineers combine their MongoDB expertise with passion, initiative, teamwork, and a great sense of humor to help our customers be successful with MongoDB. The position will be based in our Gurugram office. The standard work week will be Monday to Friday, every week. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Cool things you’ll do You'll be working alongside our largest customers, solving their complex challenges - resolving questions on architecture, performance, recovery, security, and everything in between. You'll be an expert resource on best practices in running MongoDB at scale, whatever that scale may be. You'll be an advocate for customers' needs - interfacing with our product management and development teams on their behalf. And you'll contribute to internal projects, including software development of support tools for performance, benchmarking, and diagnostics. What you need You should have 5+ years of proven experience, we consider all candidates with an eye for those who are self-taught, insatiably curious, and multi-faceted. The ideal candidates should have strong technical experience in more than one of the following areas Systems engineering experience, including Linux performance, memory management, I/O tuning, configuration, security, networking, clusters, and troubleshooting Understand core Kubernetes concepts, including containers, namespaces, custom resources and multi-cluster dep

NVIDIA is seeking a Senior Technical Program Manager to join the CSP Engagements team, focused on deep technical engagement with hyperscale cloud service providers for NVIDIA’s next‑generation datacenter systems such as Vera Rubin NVL72. This role is intended for experienced systems and embedded software leaders—including software engineering managers, technical leads, or senior architects—who have led datacenter server and platform software programs and can operate as a trusted technical partner to hyperscale CSP engineering teams. As a member of the CSP Engagements team, you will act as the primary technical engagement leader between NVIDIA’s system software organizations and CSP platform, system software, and AI teams, ensuring alignment, readiness, and successful large‑scale deployment of NVIDIA‑based datacenter solutions. What you will be doing: Lead deep technical engagements with hyperscale CSPs as the primary NVIDIA point of contact for system software, firmware, and platform readiness for NVIDIA datacenter products. Partner directly with CSP system software, firmware, and infrastructure engineering leaders to align on software architecture, bring‑up plans, deployment readiness, and production requirements for NVIDIA‑based server and rack‑scale platforms. Represent CSP technical priorities internally, advocating for customer requirements and tradeoffs across NVIDIA’s system software, firmware, hardware, silicon, and product teams are aligned to customer needs, timelines, and constraints. Own the end‑to‑end CSP engagement lifecycle, from early technical alignment and pre‑production readiness through large‑scale deployment, escalation management, and sustained production support. Drive bi‑directional technical communication: translating CSP system‑level requirements into actionable focus areas for NVIDIA engineering teams, while clearly communicating N

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 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

As Senior Data Scientist for Engineering Systems you will work independently alongside sharp, generous, and pragmatic engineers from Server Query, Atlas Clusters, and Release Quality, among other teams. Together, we tackle problems spanning resource scaling across the Atlas fleet, safe feature rollout to MongoDB clusters, automated incident response and query engine performance. Join the Platform Data Science team and help us research, prototype and ship machine learning features for MongoDB’s core server, query engine and Atlas, our database-as-a-service cloud offering. We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. What You'll Do Partner with Server Query, Atlas Clusters, Release Quality and other engineers to embed algorithmic rigor and optimization into resource scaling, release-safety and monitoring systems across the fleet and inside query engine Deliver production-ready, thoroughly tested statistical and ML algorithms with well-identified limitations that deliver measurable business impact, not just an impressive-sounding methodology Own the full feedback loop: instrument model architecture with the metrics needed to track performance and create dashboards in collaboration with our stellar analytics team, collect feedback from users and metrics to diagnose issues or opportunities, and iterate accordingly Deliver thoughtful, kind code reviews to your peers and act as a core contributor to internal packages, tooling, and team processes that increase developer productivity Measures of Success In 3 months, you’re familiar with our workflow, have an elementary understanding of our product and what teams we work with. You have delivered small-to-medium improvements to our project portfolio In 6 months, you’ve delivered one feature you researched and prototyped from scratch and demonstrated its impact on business metrics of your choice In 12 months, you've established a track record of shipping ML-driven improveme

Who You Are: The Sales Operations Technical Support Specialist provides technical support to internal and external users within a designated region. This role serves as a primary point of contact for troubleshooting, researching, and resolving website, digital platform, and online service issues escalated by sales teams and customers. The specialist is responsible for monitoring, prioritizing, and responding to support requests, identifying root causes, and ensuring timely issue resolution in accordance with established processes and service expectations. Working under general supervision, the Sales Operations Technical Support Specialist applies advanced technical knowledge and judgment to resolve complex support issues, document solutions, and escalate matters as needed. The role collaborates closely with cross-functional teams to address system and customer-impacting issues, support operational improvements, and contribute to a positive user experience.

MongoDB Technical Services Engineers use their exceptional problem solving and customer service skills, along with their deep technical experience, to advise customers and to solve their complex MongoDB problems. Technical Service Engineers are experts in the entire MongoDB ecosystem - database server, drivers, cloud and infrastructure. This also includes services such as Atlas (database as a service), or Cloud Manager (which helps customers with automation, backup and monitoring of their MongoDB systems). Our engineers combine their MongoDB expertise with passion, initiative, teamwork and a great sense of humor to help our customers to be successful with MongoDB. We are looking to speak to candidates who are interested in working out of our Dublin office under our in-office working model Monday to Friday for the first 3-6 months depending on ramping speed. Once considered ramped, they will transition to a permanent (Tuesday to Saturday) 9am-6pm work week (with 3 in-office days) to provide weekend coverage alongside other peers. Saturdays and Sundays are considered fully online workdays and not an on-call shift. Due to the 24/7 nature of our support organization, certain events throughout the year will require volunteering for coverage outside one’s normal work days or work hours (i.e. regional offsites, regional holidays, etc). These are typically announced weeks in advance with a sign-up system that considers equitability. Cool things you’ll do You'll be working alongside our largest customers, solving their complex challenges - resolving questions on architecture, performance, recovery, security, and everything in between. You'll be an expert resource on best practices in running MongoDB at scale, whatever that scale may be. You'll be an advocate for customers' needs - interfacing with our product management and development teams on their behalf. And you'll contribute to internal projects, including software development of support tools for performance, ben

About the Team OpenAI Finance is responsible for ensuring the organization is set up for success in pursuit of its mission. Within Finance, the Procurement team serves as a trusted advisor to the business, optimizing investments, securing essential resources, and enabling OpenAI’s mission through efficient and effective procurement practices. The Extended Workforce team helps OpenAI access specialized and flexible talent while creating a consistent, compliant, and high-quality experience for hiring managers, workers, vendors, and internal partners. As part of an AI-native organization, we are also rethinking how extended workforce programs should operate, using AI, automation, data, and new ways of working to reduce friction, improve decision-making, and build more scalable workforce solutions. Our goal is not simply to modernize traditional contingent workforce practices, but to help define what best-in-class extended workforce management looks like in an AI-first company. About the Role We’re looking for an experienced, hands-on Senior Manager to operate and continuously improve key elements of OpenAI’s extended workforce program. Reporting to the Head of Extended Workforce, you will be a trusted partner responsible for translating program priorities into clear plans, scalable solutions, and measurable outcomes. This is an individual contributor role with significant cross-functional ownership and influence. You will take ownership of complex workstreams, solve ambiguous operational challenges, and partner closely with our Extended Workforce Operations team, Global Compliance Lead, and cross-functional stakeholders to strengthen the systems, workflows, and partnerships that enable the program to scale globally. While operational excellence is at the heart of this role, we are equally excited about what comes next. We believe AI presents an opportunity to fundamentally rethink how extended workforce programs operate. We are looking for someone who enjoys challengin