Node Js Jobs

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand. Node Infra owns the full lifecycle of accelerator capacity at Anthropic. We ingest and provision compute from all major cloud providers and from datacenters custom-built for Anthropic, stand up and scale the clusters behind one of the industry's largest AI compute fleets, and build the health, diagnostics and repair automation that keep every GPU, TPU and Trainium node in the fleet usable and ready to power Anthropic's frontier AI research. Key responsibilities Own the technical strategy and roadmap for node lifecycle management - ingestion, bring-up, health checking, and automated repair Drive cross-team initiatives to build and scale AI clusters across multiple clouds and accelerator families Design and operate the systems that detect, isolate, and remediate unhealthy hardware automatically, driving up fleet MTBI and minimizing stranded capacity Define infrastructure architecture, ensuring the hardest problems get solved - whether by you directly or by working through others Work closely with cloud providers and internal research/inference/product teams to shape long-term compute, data, and infrastructure strategy Establish and evolve operational excellence practices (incident response, postmortem culture, on-

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand. Node Infra owns the full lifecycle of accelerator capacity at Anthropic. We ingest and provision compute from all major cloud providers and from datacenters custom-built for Anthropic, stand up and scale the clusters behind one of the industry's largest AI compute fleets, and build the health, diagnostics and repair automation that keep every GPU, TPU and Trainium node in the fleet usable and ready to power Anthropic's frontier AI research. Key responsibilities Own the technical strategy and roadmap for node lifecycle management - ingestion, bring-up, health checking, and automated repair Drive cross-team initiatives to build and scale AI clusters across multiple clouds and accelerator families Design and operate the systems that detect, isolate, and remediate unhealthy hardware automatically, driving up fleet MTBI and minimizing stranded capacity Define infrastructure architecture, ensuring the hardest problems get solved - whether by you directly or by working through others Work closely with cloud providers and internal research/inference/product teams to shape long-term compute, data, and infrastructure strategy Establish and evolve operational excellence practices (incident response, postmortem culture, on-

Engineer, Node Development PE — Boise, ID - Main Site. Apply via Workday.

Sr. Node Development Product Engineer - DRAM Technology — Boise, ID - Main Site. Apply via Workday.

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role Data Products integrates GitLab and third-party SDLC data, and builds the dashboards, APIs, and data products that turn it into trusted, interoperable intelligence for customers and internal teams. This is a 0 to 1 team and we are hiring for a foundational engineering role. That means you bring technical leadership through ambiguity, helping figure out what to build, making the foundational design decisions, and keeping delivery moving while the picture is still forming. You own the full lifecycle of what ships and stand behind it. What you'll bring Proven ability to influence as a Staff owning product or

MTS/Principal Engineer, Wet Process Engineering, NAND Advance Node — Fab 10N/X, Singapore. Apply via Workday.

*]:pointer-events-auto R6Vx5W_threadScrollVars scroll-mb-[calc(var(--scroll-root-safe-area-inset-bottom,0px)+var(--thread-response-height))] scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" data-turn-id="request-6a61cc6f-a00c-8334-82ca-8a2dd2e477ca-0" data-turn-id-container="request-6a61cc6f-a00c-8334-82ca-8a2dd2e477ca-0" data-testid="conversation-turn-4" data-turn="assistant"> About the job Shape how advanced AI hardware is tested before it reaches customers. You'll lead the technical direction of manufacturing test solutions for Host Processor Modules, Server Blades, and multi-node rack systems. Your work will help ensure every system meets the highest quality standards before deployment. You'll own the architecture of the test executive software and develop manufacturing test content that validates complex hardware at scale. Working across hardware, firmware, and software teams, you'll enable reliable, efficient testing throughout production. This role offers broad technical influence. You'll solve complex engineering challenges, improve manufacturing quality through data, and help shape the future of Graphcore's production test capability. The team and culture You'll join the Product Test and Diagnosis team within Manufacturing Operations. The team defines and delivers test strategies across silicon, boards, server systems, and rack-scale platforms. Day to day, you'll work closely with engineers across hardware, firmware, software, manufacturing, and quality. Decisions are driven by technical evidence, collaboration, and continuous improvement. You'll have the freedom to lead technically, mentor other engineers, and influence how manufacturing test evolves across globally distributed teams. What we're looking for Essential Extensive experience developing and deploying manufacturing test solutions for high-performance servers, accelerators (GPU-class), or comparable large-scale compute hardware. Proven technical leadership as

About the job Build the test systems that help deliver AI hardware at production scale. As a Staff Hardware System Test Engineer, you'll develop manufacturing test solutions for complex compute systems. Your work will help ensure products reach customers with the quality and reliability expected from Graphcore. You'll shape how hardware is tested across Host Processor Modules, server blades, and multi-node racks. The tools, test content, and diagnostics you create will directly influence manufacturing efficiency and product quality. You'll develop test software, design test approaches, and solve challenging hardware issues. You'll work closely with hardware, firmware, software, and manufacturing teams to improve test coverage and diagnose problems quickly. This role offers broad technical scope across silicon, boards, systems, software, and manufacturing. You'll have the opportunity to influence engineering decisions and raise technical standards across the organisation. The team and culture The Product Test and Diagnosis team owns the strategy for finding and diagnosing hardware defects throughout the product lifecycle. The team works across silicon, boards, servers, and rack-scale systems. Day to day, engineers work closely with design, firmware, software, quality, and manufacturing teams. Problems are solved through data, technical debate, and hands-on investigation. You'll join a global engineering group spanning the UK, Taiwan, India, and the United States. People are trusted to take ownership, make decisions, and drive improvements that deliver measurable results. What we're looking for Essential: Significant experience developing and deploying manufacturing test solutions for high-performance servers, accelerators (GPU-class), or comparable large-scale compute hardware. Strong technical leadership as an individual contributor, with experience owning substantial technical workstreams and collab

NVIDIA is at the forefront of the generative AI revolution, building the software and systems that power the world’s most advanced large language model workloads. We are looking for a Software Engineer focused on bring-up, triage, benchmarking, analysis, and optimization of distributed training and inference workloads across NVIDIA GPU platforms at the largest scales we run. In this role you will help bring up, benchmark, and debug distributed LLM workloads on multi-GPU and multi-node deployments, and own the design and implementation of the benchmarking tooling, automation, and debugging workflows that support them. This is a hands-on role for an engineer who enjoys deep technical problems across deep learning systems, GPU performance, distributed computing, and large-scale operations. What you’ll be doing: Bring up, validate, and debug large-scale AI clusters, infrastructure, and end-to-end workloads. Bring up, tune, and benchmark AI pre-training, post-training, and inference workloads using PyTorch, NeMo / Megatron, TensorRT-LLM, and adjacent NVIDIA AI software stacks. Perform root-cause analysis of failures in large distributed environments Contribute to the resilience and failure-attribution tooling that detects, triages, and attributes node, fabric, and workload failures across the cluster. Build and maintain repeatable benchmark suites, automation, acceptance criteria, and qualification workflows on new platforms. Tune runtime settings, communication parameters, and deployment configurations in close partnership with framework, systems, and platform teams. Deliver actionable, data-driven recommendations based on profiling, benchmark results, and cluster characterization. What we ne

Join Cluster Scalability, one of MongoDB's Online Transaction Processing teams, and help build the core infrastructure that makes MongoDB a world-class distributed database. The team builds the infrastructure and tools that let customers scale their workloads past what a single node can handle. We take pride in building clean abstractions over hard distributed systems problems, so users can focus on their data instead of worrying about where it lives or how it's accessed. Our work has a big impact: it solves the hardest data challenges faced by MongoDB's largest customers. As a Senior Software Engineer on Cluster Scalability, you'll work on data partitioning, one of the hardest and most impactful problem areas at MongoDB today. You'll collaboratively design and build the distributed machinery that turns independent query-processing and storage nodes into a single, unified database system. Your team’s work will be to build the data-movement and dynamic-scaling features that run on top of it. Current work includes seamless horizontal scaling with minimal tradeoffs, better cluster elasticity and smarter workload execution. You'll solve complex performance problems and design protocols for moving and placing data without disruption. Your work will help the architecture scale reliably to meet customer demand at any volume. Our team champions a strong culture of inclusivity, diversity, and collaboration. If you want to work on a collaborative team that applies distributed systems fundamentals to deliver core features of a popular database, join us! Let’s change what’s possible for application developers, system architects, and database operators. This role can be based remotely in the United States. Candidate Profile 5+ years of experience building distributed systems Experience with building production-level code with a large user base, robust design structure and rigorous code quality, written in C++. Degree in Computer Science or similar field, or equivalent practical

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<

What We’re Looking For: We’re looking for DFT engineers to contribute to and own DFT efforts for blocks and entire dies on the A-0 and A-1 wafer-scale systems. Ideal Background: Experience leading DFT efforts for multiple advanced node SoC tapeouts Nice to Have: Experience leading DFT efforts for large die area (eg reticle-max) chips Experience leading DFT efforts for multi-die/multi-chiplet/MCM designs Experience leading DFT efforts for AI accelerator SoCs

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is looking for a mid- to senior-level Physical Design Engineer with a strong background in static timing analysis (STA). In this role, you will help converge multi-million-gate designs on advanced process nodes and partner with cross-functional teams through final signoff and tapeout. This role is hybrid , based out of Austin, TX, Fort Collins, CO, or Santa Clara, CA . We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A physical design engineer with 8+ years of experience in STA, timing closure, and advanced-node design implementation. Experienced with timing flows, constraints, clocking, CDC, RDC, derates, uncertainties, guardbanding, and final signoff. Skilled in writing and debugging SDC constraints, creating ECOs, developing closure strategies, and analyzing worst-case corners. A strong collaborator and communicator who can drive results across distributed, cross-functional engineering teams. What We Need Drive timing convergence across blocks, partitions, sections, and top-level designs; generate and validate timing models and publish results. Analyze timing violations, develop and propagate fixes, debug timing-flow issues, and

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Focus on technology node development to advance next-generation DRAM technologies. Contribute to DRAM product design to enable effective transfer of node development innovations into production products. Collaborate with product engineering and process technology teams to validate designs and help guide technology direction. Perform circuit design and floor planning, including power delivery network (PDN) design. Conduct simulation, debugging, and root cause analysis of design and process issues. Identify failures and provide corrective feedback to block design owners. Deliver design insights and recommendations to Technology Development process teams. Validating device and schematic functionality using memory testing systems. Requirements: Employer will accept a Master’s degree in Electrical Engineering, Computer Engineering, or related field and 2 years of work experience in job offered or in a related occupation. Position requires: 1. CMOS Circuit Design; 2. Digital Logic; 3. Mixed Signal Design; 4. Sense Amplifier; 5. Clock or Data Path; 6. AOCV; 7. Power, IR Drop, or PDN; 8. DFT; 9. Spice or Spectre; 10. Verilog; 11. Parasitic Extraction or SPEF; 12. Floor planning or Routing; 13. Cadence Virtuoso; 14. Python; and 15. Data Analysis (JMP). As a world leader in the semiconductor industry, Micron is dedicated to your personal wellbeing and profes

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Key Responsibilities The Layout Senior Manager leads layout planners and engineers to develop layout strategies and solutions for fab scale expansion, technology node migration, space optimization, and operational efficiency improvement. This role is responsible for maximizing fab space utilization while balancing operational flexibility, cost effectiveness, expansion readiness, and future manufacturing requirements. The Layout Senior Manager drives intelligent layout planning, digital transformation, and data-driven decision making through advanced modeling, simulation, automation, and AI-enabled solutions. This position also develops long-term space planning strategies and cross-site optimization methodologies to support Micron's business growth and manufacturing competitiveness. Drive Benchmarking Capabilities Align layout planning practices, space utilization performance, and expansion project execution to meet or exceed Micron and industry benchmarking standards. Regularly report layout, space efficiency, and expansion project metrics through established review processes. Maintain ongoing collaboration with global Layout, Planning, Operations, and Manufacturing teams to identify and implement Best Known Methods (BKMs). Partner with Planning, Manufacturing, Facilities and AMHS teams to model fab growth scenarios, space utilization, and future capacity requirements. Identify future space, infrastructure, and operational constraints before