As a Solutions Architect at CoreWeave, you will play a vital role in helping customers succeed with our cloud infrastructure offerings, focusing on Kubernetes solutions within high-performance compute (HPC) environments.
\nYour responsibilities will include serving as the primary technical point of contact for customers, establishing strong technical relationships and ensuring their success with CoreWeave's cloud infrastructure offerings.
\nYou will collaborate closely with customers to understand their unique business needs and create, prototype, and deploy tailored solutions that align with their requirements.
\nYou will lead proof of concept initiatives to showcase the value and viability of CoreWeave's solutions within specific environments.
\nYou will drive technical leadership and direction during customer meetings, presentations, and workshops, addressing any technical queries or concerns that arise.
\nYou will act as a virtual member of CoreWeave's Kubernetes product and engineering teams, identifying opportunities for product enhancement and collaborating with engineers to implement your suggestions.
\nYou will offer valuable insights on product features, functionality, and performance, contributing regularly to discussions about product strategy and architecture.
\nYou will conduct periodic technical reviews and assessments of customer workloads, pinpointing opportunities for workload optimization and suggesting suitable solutions.
\nYou will stay informed of the latest developments and trends in Kubernetes, cloud computing and infrastructure, sharing your thought leadership with customers and internal stakeholders.
\nYou will lead the prototyping and initiation of research and development efforts for emerging products and solutions, delivering prototypes and key insights for internal consumption.
\nYou will represent CoreWeave at conferences and industry events, with occasional travel as required.
\nTo be successful in this role, you will need to have a B.S. in Computer Science or a related technical discipline, or equivalent experience.
\nYou will also need to have 7+ years of proven experience as a Solutions Architect, engineer, researcher, or technical account manager in cloud infrastructure, focusing on building distributed systems or HPC/cloud services, with an expertise focused on scalable Kubernetes solutions.
\nYou will need to be fluent in cloud computing concepts, architecture, and technologies with hands-on experience in designing and implementing cloud solutions.
\nYou will need to have a proven track record with building customer relationships, communicating clearly and the ability to break down complex technical concepts to both technical and non-technical audiences.
\nYou will need to be familiar with NVIDIA GPUs typically used in AI/ML applications and associated technologies such as Infiniband and NVIDIA Collective Communications Library (NCCL).
\nYou will need to have experience with running large-scale Artificial Intelligence/Machine Learning (AI/ML) training and inference workloads on technologies such as Slurm and Kubernetes.
\nPreferred qualifications include code contributions to open-source inference frameworks, experience with scripting and automation related to Kubernetes clusters and workloads, experience with building solutions across multi-cloud environments, and client or customer-facing publications/talks on latency, optimization, or advanced model-server architectures.
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\nIn this role, you will:
\nServe as the primary technical point of contact for customers, establishing strong technical relationships and ensuring their success with CoreWeave's cloud infrastructure offerings, focusing on networking technologies within high-performance compute (HPC) environments Collaborate closely with customers to understand their unique business needs and create, prototype, and deploy tailored solutions that align with their requirements. Lead proof of concept initiatives to showcase the value and viability of CoreWeave's solutions within specific environments. Drive technical leadership and direction during customer meetings, presentations, and workshops, addressing any technical queries or concerns that arise. Act as a virtual member of CoreWeave's Networking product and engineering teams, identifying opportunities for product enhancement and collaborating with engineers to implement your suggestions. Offer valuable insights on product features, functionality, and performance, contributing regularly to discussions about product strategy and architecture. Conduct periodic technical reviews and assessments of customer workloads, pinpointing opportunities for workload optimization and suggesting suitable solutions. Stay informed of the latest developments and trends in Kubernetes, cloud computing and infrastructure, sharing your thought leadership with customers and internal stakeholders. Lead the prototyping and initiation of research and development efforts for emerging products and solutions, delivering prototypes and key insights for internal consumption. Represent CoreWeave at conferences and industry events, with occasional travel as required.
\nWho You Are:
\nB.S. in Computer Science or a related technical discipline, or equivalent experience 7+ years of proven experience as a Solutions Architect, engineer, researcher, or technical account manager in cloud infrastructure focusing on building distributed systems or HPC/cloud services, with an expertise focused on infrastructure networking. Fluency in cloud computing concepts, architecture, and technologies with hands-on experience in designing and implementing cloud solutions Proven track record with building customer relationships, communicating clearly and the ability to break down complex technical concepts to both technical and non-technical audiences Expertise with a broad range of networking technologies and topics, with a familiarity to understand the needs and use cases is it relates to securing and enabling high performance networking environments. Experience with managing infrastructure networking, Kubernnetes CSI management, and private networking concepts Familiar with NVIDIA GPUs typically used in AI/ML applications and associated technologies such as Infiniband and NVIDIA Collective Communications Library (NCCL)
\nPreferred:
\nCode contributions to open-source inference frameworks Experience with scripting and automation related to network technologies Experience with building solutions across multi-cloud environments Client or customer-facing publications/talks on latency, optimization, or advanced model-server architectures
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\nStrong candidates will have a track record of solving large-scale systems problems and low-level optimization. They should have significant experience optimizing ML systems for TPUs, GPUs, or other accelerators, and be results-oriented with a bias towards flexibility and impact.
\nResponsibilities:
\nRequirements:
\nBenefits:
\nNote: This job description is a rewritten version of the original ad, focusing on the key responsibilities, requirements, and benefits.
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\nCollaborate closely with customers to understand their unique business needs and create, prototype, and deploy tailored solutions that align with their requirements. Lead proof of concept initiatives to showcase the value and viability of CoreWeave's solutions within specific environments.
\nDrive technical leadership and direction during customer meetings, presentations, and workshops, addressing any technical queries or concerns that arise. Act as a virtual member of CoreWeave's Kubernetes product and engineering teams, identifying opportunities for product enhancement and collaborating with engineers to implement your suggestions.
\nOffer valuable insights on product features, functionality, and performance, contributing regularly to discussions about product strategy and architecture. Conduct periodic technical reviews and assessments of customer workloads, pinpointing opportunities for workload optimisation and suggesting suitable solutions.
\nStay informed of the latest developments and trends in Kubernetes, cloud computing and infrastructure, sharing your thought leadership with customers and internal stakeholders. Lead the prototyping and initiation of research and development efforts for emerging products and solutions, delivering prototypes and key insights for internal consumption.
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\nRequirements:
\nNice to have:
\nRepresentative projects:
\nNote: The salary range for this position is $280,000-$850,000 USD per year.
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\nAbout the Team
\nWe build foundational AI infrastructure that enables large-scale training and inference across diverse workloads and rapidly evolving hardware generations. Our work directly shapes how AI systems are designed, deployed, and scaled today and into the future. Engineers on this team operate with end-to-end ownership, deep technical rigor, and a strong bias toward real-world impact.
\nMicrosoft Superintelligence Team
\nMicrosoft Superintelligence team’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
\nThis role is part of Microsoft AI’s Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society—advancing science, education, and global well-being. We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact. If you’re a brilliant, highly-ambitious and low ego individual, you’ll fit right in—come and join us as we work on our next generation of models!
\nResponsibilities
\nLead the co-design of AI systems across hardware and software boundaries, spanning accelerators, interconnects, memory systems, storage, runtimes, and distributed training/inference frameworks. Drive architectural decisions by analyzing real workloads, identifying bottlenecks across compute, communication, and data movement, and translating findings into actionable system and hardware requirements. Co-design and optimize parallelism strategies, execution models, and distributed algorithms to improve scalability, utilization, reliability, and cost efficiency of large-scale AI systems. Develop and evaluate what-if performance models to project system behavior under future workloads, model architectures, and hardware generations, providing early guidance to hardware and platform roadmaps. Partner with compiler, kernel, and runtime teams to unlock the full performance of current and next-generation accelerators, including custom kernels, scheduling strategies, and memory optimizations. Influence and guide AI hardware design at system and silicon levels, including accelerator microarchitecture, interconnect topology, memory hierarchy, and system integration trade-offs. Lead cross-functional efforts to prototype, validate, and productionize high-impact co-design ideas, working across infrastructure, hardware, and product teams. Mentor senior engineers and researchers, set technical direction, and raise the overall bar for systems rigor, performance engineering, and co-design thinking across the organization.
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\nWe pursue this mission through deep hardware–software co-design, combining rigorous systems thinking with hands-on engineering. The team invests heavily in understanding real production workloads large-scale training, inference, and emerging multimodal models and translating those insights into concrete improvements across the stack: from kernels, runtimes, and distributed systems, all the way down to silicon-level trade-offs and datacenter-scale architectures.
\nThis role sits at the boundary between exploration and production. You will work closely with internal infrastructure, hardware, compiler, and product teams, as well as external partners across the hardware and systems ecosystem. Our operating model emphasizes rapid ideation and prototyping, followed by disciplined execution to drive high-leverage ideas into production systems that operate at massive scale.
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\nMicrosoft Superintelligence Team\nMicrosoft Superintelligence team’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
\nThis role is part of Microsoft AI’s Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society—advancing science, education, and global well-being. We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact.
\nResponsibilities\nLead the co-design of AI systems across hardware and software boundaries, spanning accelerators, interconnects, memory systems, storage, runtimes, and distributed training/inference frameworks.
\nDrive architectural decisions by analyzing real workloads, identifying bottlenecks across compute, communication, and data movement, and translating findings into actionable system and hardware requirements.
\nCo-design and optimize parallelism strategies, execution models, and distributed algorithms to improve scalability, utilization, reliability, and cost efficiency of large-scale AI systems.
\nDevelop and evaluate what-if performance models to project system behavior under future workloads, model architectures, and hardware generations, providing early guidance to hardware and platform roadmaps.
\nPartner with compiler, kernel, and runtime teams to unlock the full performance of current and next-generation accelerators, including custom kernels, scheduling strategies, and memory optimizations.
\nInfluence and guide AI hardware design at system and silicon levels, including accelerator microarchitecture, interconnect topology, memory hierarchy, and system integration trade-offs.
\nLead cross-functional efforts to prototype, validate, and productionize high-impact co-design ideas, working across infrastructure, hardware, and product teams.
\nMentor senior engineers and researchers, set technical direction, and raise the overall bar for systems rigor, performance engineering, and co-design thinking across the organization.
\nQualifications\nBachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
\nAdditional or Preferred Qualifications\nMaster’s Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor’s Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
\nStrong background in one or more of the following areas: AI accelerator or GPU architectures Distributed systems and large-scale AI training/inference High-performance computing (HPC) and collective communications ML systems, runtimes, or compilers Performance modeling, benchmarking, and systems analysis Hardware–software co-design for AI workloads Proficiency in systems-level programming (e.g., C/C++, CUDA, Python) and performance-critical software development.
\nProven ability to work across organizational boundaries and influence technical decisions involving multiple stakeholders. Experience designing or operating large-scale AI clusters for training or inference. Deep familiarity with LLMs, multimodal models, or recommendation systems, and their systems-level implications. Experience with accelerator interconnects and communication stacks (e.g., NCCL, MPI, RDMA, high-speed Ethernet or InfiniBand). Background in performance modeling and capacity planning for future hardware generations. Prior experience contributing to or leading hardware roadmaps, silicon bring-up, or platform architecture reviews. Publications, patents, or open-source contributions in systems, architecture, or ML systems are a plus.
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\nPioneering the next generation of AI requires breakthrough innovations in GPU performance and systems engineering. As a GPU Performance Engineer, you'll architect and implement the foundational systems that power Claude and push the frontiers of what's possible with large language models. You'll be responsible for maximizing GPU utilization and performance at unprecedented scale, developing cutting-edge optimizations that directly enable new model capabilities and dramatically improve inference efficiency.
\nWorking at the intersection of hardware and software, you'll implement state-of-the-art techniques from custom kernel development to distributed system architectures. Your work will span the entire stack—from low-level tensor core optimizations to orchestrating thousands of GPUs in perfect synchronization.
\nStrong candidates will have a track record of delivering transformative GPU performance improvements in production ML systems and will be excited to shape the future of AI infrastructure alongside world-class researchers and engineers.
\nYou might be a good fit if you:
\nStrong candidates may also have experience with:
\nRepresentative projects:
\nDeadline to apply: None. Applications will be reviewed on a rolling basis.
\nThe expected salary range for this position is:
\nAnnual Salary: $280,000 - $850,000USD
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\nSoftware Engineer, Collective Communication
\nLocation
\nSan Francisco
\nEmployment Type
\nFull time
\nDepartment
\nScaling
\nCompensation
\nThe base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.
\nMore details about our benefits are available to candidates during the hiring process.
\nThis role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.
\nAbout the Team
\nThe Workload Networking team is responsible for the collective communication stack used in our largest training jobs. Using a combination of C++ and CUDA we work on novel collective communication techniques that enable efficient training of our flagship models on our largest custom built supercomputers.
\nThe models we train are key ingredients to the AI research progress at OpenAI and the field as a whole, and we continually incorporate learnings from our entire research org into our training platform.
\nAbout the Role
\nAs a Software Engineer, Networking you will design and implement custom networking collectives that are tightly integrated into our training stack.
\nWe’re looking for people who have a background in low level performance critical software. Experience with collective communication is a bonus.
\nThis role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
\nIn this role, you will:
\nYou might thrive in this role if you:
\nAbout OpenAI
\nOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
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