Your 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.

You will collaborate closely with customers to understand their unique business needs and create, prototype, and deploy tailored solutions that align with their requirements.

You will lead proof of concept initiatives to showcase the value and viability of CoreWeave's solutions within specific environments.

You will drive technical leadership and direction during customer meetings, presentations, and workshops, addressing any technical queries or concerns that arise.

You 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.

You will offer valuable insights on product features, functionality, and performance, contributing regularly to discussions about product strategy and architecture.

You will conduct periodic technical reviews and assessments of customer workloads, pinpointing opportunities for workload optimization and suggesting suitable solutions.

You will stay informed of the latest developments and trends in Kubernetes, cloud computing and infrastructure, sharing your thought leadership with customers and internal stakeholders.

You will lead the prototyping and initiation of research and development efforts for emerging products and solutions, delivering prototypes and key insights for internal consumption.

You will represent CoreWeave at conferences and industry events, with occasional travel as required.

To be successful in this role, you will need to have a B.S. in Computer Science or a related technical discipline, or equivalent experience.

You 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.

You will need to be fluent in cloud computing concepts, architecture, and technologies with hands-on experience in designing and implementing cloud solutions.

You 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.

You 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).

You 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.

Preferred 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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In this role, you will:

Serve 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.

Who You Are:

B.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)

Preferred:

Code 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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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 Kubernetes 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 optimisation 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.

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You will work closely with customers, data center technicians, and engineering teams to ensure the reliability, performance, and scalability of our infrastructure.

Key responsibilities include:

• Providing high-level support for customers utilizing bare-metal GPU fleets on CoreWeave Cloud.
• Diagnosing, triaging, and investigating reported customer issues and high-priority incidents, identifying root causes and escalating when necessary.
• Developing a deep understanding of customer workloads and use cases to provide tailored technical support.
• Coordinating remote troubleshooting and hardware interventions with Data Center Technicians.
• Creating and maintaining internal documentation, including troubleshooting guides, best practices, and knowledge base articles.
• Participating in an on-call rotation to support production clusters and ensure operational reliability.
• Collaborating with engineering teams to improve hardware reliability, software stability, and system performance.
• Implementing automation and scripting to streamline support workflows and reduce manual interventions.
• Performing in-depth log analysis and debugging across multiple layers of the stack (firmware, drivers, hardware).
• Providing feedback to internal teams on common support issues to drive continuous improvements.
• Working with networking teams to troubleshoot connectivity issues affecting customer workloads.
• Supporting supercomputing infrastructure running GPU workloads at scale.
• Driving operational excellence by refining internal processes and support methodologies.

To succeed in this role, you will need:

• Experience in data centers, GPU clusters, server deployments, system administration, or hardware troubleshooting.
• Demonstrated experience driving resolutions and continuous improvements across cross-functional environments and teams within a data center environment.
• Intermediate knowledge of Linux (Ubuntu, CentOS, or similar), including command-line proficiency.
• Experience with NVIDIA GPUs, SuperMicro systems, Dell systems, high-performance computing (HPC), and large-scale data center environments.
• Experience in networking fundamentals (TCP/IP, VLANs, DNS, DHCP) and troubleshooting tools.
• Hands-on experience with firmware updates, BIOS configurations, and driver management.
• Experience analyzing system logs and debugging issues across firmware, drivers, and hardware layers.
• Experience working with Jira, Confluence, Notion, or other issue-tracking and documentation platforms.
• Experience in scripting and automation (Python, Bash, Ansible, or similar).

If you're a curious and analytical individual with a passion for problem-solving and a desire to work in a fast-paced environment, we'd love to hear from you!

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As part of the Solutions Architecture team, we work with some of the most exciting computing hardware and software technologies including the latest breakthroughs in machine learning and data science. A Solutions Architect is the first line of technical expertise between NVIDIA and our customers so you will engage directly with developers, researchers, and data scientists with some of NVIDIA's most strategic technology customers as well as work directly with business and engineering teams on product strategy.

What you will be doing:

• Working with Cloud Service Providers to develop and demonstrate solutions based on NVIDIA's ML/DL and data science software and hardware technologies

• Build and deploy AI/ML solutions at scale using NVIDIA's AI software on cloud-based GPU platforms.

• Build custom PoCs for solution that address customer's critical business needs applying NVIDIA hardware and software technology

• Partner with Sales Account Managers or Developer Relations Managers to identify and secure new business opportunities for NVIDIA products and solutions for ML/DL and other software solutions

• Prepare and deliver technical content to customers including presentations about purpose-built solutions, workshops about NVIDIA products and solutions, etc.

• Conduct regular technical customer meetings for project/product roadmap, feature discussions, and intro to new technologies. Establish close technical ties to the customer to facilitate rapid resolution of customer issues

What we need to see:

• 3+ years of Solutions Engineering (or similar Sales Engineering roles) or equivalent experience

• 3+ years of work-related experience in Deep Learning and Machine Learning, including deep learning frameworks TensorFlow or PyTorch, GPU, and CUDA experience extremely helpful.

• BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Statistics, Physics, or other Engineering fields or equivalent experience.

• Established track record of deploying solutions in cloud computing environments including AWS, GCP, or Azure

• Knowledge of DevOps/ML Ops technologies such as Docker/containers, Kubernetes, data center deployments

• Ability to use at least one scripting language (i.e., Python)

• Good programming and debugging skills

• Ability to communicate your ideas/code clearly through documents, presentation etc.

Ways to stand out from the crowd:

• AWS, GCP or Azure Professional Solution Architect Certification.

• Hands-on experience with NVIDIA GPUs and SDKs (e.g. CUDA, RAPIDS, Triton etc.)

• System-level experience specifically GPU-based systems

• Experience with Deep Learning at scale

• Familiarity with parallel programming and distributed computing platforms

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Responsibilities:

• 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.
• Participate in and contribute 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.
• Create proof-of-concepts to evaluate and motivate extensions in programming models, new designs in runtimes and new features in hardware.

Requirements:

• 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 system architecture and operating systems.
• Experience with parallel programming interfaces and communication runtimes.
• Ability and flexibility to work and communicate effectively in a multi-national, multi-time-zone corporate environment.

Nice to Have:

• Deep understanding of technology and passionate about what you do.
• Experience with CUDA programming and NVIDIA GPUs.
• Knowledge of high-performance networks like InfiniBand, iWARP etc.
• Experience with HPC applications.
• Experience with Deep Learning Frameworks such PyTorch, TensorFlow, etc.
• Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic matrix environment.

Benefits:

• Highly competitive salaries.
• Comprehensive benefits package.
• Eligibility for equity.
• Opportunity to work with a world-class engineering team.
• Ability to work in a dynamic matrix environment.
• Opportunity to contribute to cutting-edge technology.
• Flexible work arrangements.
• Professional development opportunities.

How to Apply:

Applications for this job will be accepted at least until March 13, 2026. NVIDIA uses AI tools in its recruiting processes.

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The ML Infrastructure team at Cursor builds large-scale compute, storage, and software infrastructure to support the company's work building the world's best agentic coding model. We're looking for strong engineers who are interested in building high-performance infrastructure and the software to support it. This role works closely with ML researchers and engineers to enable their work through improvements to our training framework, systems reliability/performance, and developer experience.

What you'll do

• Collaborate with ML researchers to improve the throughput and reliability of training
• Work with OEMs, cloud service providers, and others to plan and build cutting-edge GPU infrastructure
• Improve the density and scalability of compute environments to enable increasingly large RL workloads
• Create software and systems to automate building, monitoring, and running GPU clusters
• Build workload scheduling and data movement systems to support Cursor's growing training footprint

You may be a fit if

• A strong background in systems and infrastructure-focused software engineering, particularly in Python, Typescript, Rust, and Golang
• Experience with distributed storage and networking infrastructure, particularly on Linux systems across cloud and bare metal environments
• Exposure to large-scale systems and their unique challenges, ideally across thousands of nodes with significant resource footprints

Nice to have

• Operational exposure to Nvidia GPUs with Infiniband or RoCE, particularly with Blackwell and Hopper-class hardware
• Exposure to Ray, Slurm, or other common compute and runtime schedulers

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Location

San Francisco

Employment Type

Full time

Department

Scaling

Compensation

• $455K – $555K

The 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.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This 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.

About the Team

Our Inference team brings OpenAI’s most capable research and technology to the world through our products. We empower consumers, enterprise and developers alike to use and access our start-of-the-art AI models, allowing them to do things that they’ve never been able to before. We focus on performant and efficient model inference, as well as accelerating research progression via model inference.

About the Role

We are looking for an engineering leader who wants to build and lead the worlds leading AI systems and modeling engineers who take the world's largest and most capable AI models and optimize them for use in a high-volume, low-latency, and high-availability production and research environment.

In this role, you will:

• Lead a team of engineers who are experts in working with distributed systems, with a deep understanding of model architecture, system co-design with research and production team,

• Work alongside partners in machine learning researchers, engineers, and product managers to bring our latest technologies into production.

• Work in an outcome-oriented environment where everyone contributes across layers of the stack, from infra plumbing to performance tuning.

• Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of our model inference stack.

• Build tools to give us visibility into our bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues.

• Optimize our code and fleet of GPU’s to utilize every FLOP and every GB of GPU RAM of our hardware.

You might thrive in this role if you:

• Have an understanding of modern ML architectures and an intuition for how to optimize their performance, particularly for inference.

• Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done.

• Have at least 15 years of professional software engineering experience.

• Have or can quickly gain familiarity with PyTorch, NVidia GPUs and the software stacks that optimize them (e.g. NCCL, CUDA), as well as HPC technologies such as InfiniBand, MPI, NVLink, etc.

• Have experience architecting, building, observing, and debugging production distributed systems. Bonus point if worked on performance-critical distributed systems.

• Have needed to rebuild or substantially refactor production systems several times over due to rapidly increasing scale.

• Are self-directed and enjoy figuring out the most important problem to work on.

• Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed.

About OpenAI

OpenAI 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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Location

San Francisco

Employment Type

Full time

Department

Scaling

Compensation

• $295K – $555K • Offers Equity

The 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.

Benefits

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

About the Team

Our Inference team brings OpenAI’s most capable research and technology to the world through our products. We empower consumers, enterprise and developers alike to use and access our start-of-the-art AI models, allowing them to do things that they’ve never been able to before. We focus on performant and efficient model inference, as well as accelerating research progression via model inference.

About the Role

We are looking for an engineer who wants to take the world's largest and most capable AI models and optimize them for use in a high-volume, low-latency, and high-availability production and research environment.

In this role, you will:

• Work alongside machine learning researchers, engineers, and product managers to bring our latest technologies into production.

• Work alongside researchers to enable advanced research through awesome engineering.

• Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of our model inference stack.

• Build tools to give us visibility into our bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues.

• Optimize our code and fleet of Azure VMs to utilize every FLOP and every GB of GPU RAM of our hardware.

You might thrive in this role if you:

• Have an understanding of modern ML architectures and an intuition for how to optimize their performance, particularly for inference.

• Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done.

• Have at least 5 years of professional software engineering experience.

• Have or can quickly gain familiarity with PyTorch, NVidia GPUs and the software stacks that optimize them (e.g. NCCL, CUDA), as well as HPC technologies such as InfiniBand, MPI, NVLink, etc.

• Have experience architecting, building, observing, and debugging production distributed systems. Bonus point if worked on performance-critical distributed systems.

• Have needed to rebuild or substantially refactor production systems several times over due to rapidly increasing scale.

• Are self-directed and enjoy figuring out the most important problem to work on.

• Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed.

About OpenAI

OpenAI 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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