We are the GPU Communications Libraries and Networking team at NVIDIA. We deliver communication libraries like NCCL, NVSHMEM, UCX for Deep Learning and HPC. DL and HPC applications have a huge compute demand already 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! We are looking for a technical leader to manage our NVSHMEM and UCX libraries. This is an outstanding opportunity to push the limits on the state-of-the-art and deliver platforms the world has never seen before. Are you ready for to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Lead, mentor, and grow your library engineering team and be responsible for the planning and execution of projects as well as the quality, and performance of your libraries. This is a technical leadership role so you will participate in feature design and implementation. Interact with internal and external partners and researchers to understand their use cases and requirements. Collaborate with engineering teams, program and product management, and partners to define the product roadmap. Continuously review and identify improvement opportunities in established processes, infrastructure, and practices to ensure the teams are executing in the most efficient and transparent manner. What we need to see: 10+ overall years of experience in the software industry with specialization in HPC networking or system software. 4+ years of management experience. BS, MS, or Ph.D. in C

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this team? The GPU Clusters team builds and operates the superclusters that train Cohere’s frontier models. We sit at the intersection of hardware, distributed systems, and AI research. We work with cloud providers, researchers, and other infrastructure teams on problems few companies get to take on. As an Engineering Manager, you’ll lead a team of engineers who care deeply about GPU infrastructure. You’ll set technical direction, grow people, and help the company scale a rapidly growing compute footprint. As an Engineering Manager, you will: Hire, mentor, and grow a team of GPU infrastructure engineers , including performance, career development, and technical guidance on hard infrastructure problems Own the technical roadmap for the fleet: how we deploy, operate, and scale Kubernetes clusters, including workload scheduling, hardware fault detection, and performance Partner with researchers and ML engineers so the training and inference stack works well on new GPU architectures Work with cross-functional stakeholders such as Capacity, Finance, Legal, Security, and other infrastructure teams on planning, cost, compliance, an

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and establish teams with the most thoughtful people in the world. We are looking for an excellent engineering manager to own and deliver an end to end manageability stack for Data Center Systems. We are seeking an experienced manager who is deeply technical, hands-on, and has a wide system view. You will manage a team of experts, design & build OpenBMC based manageability software stack for NVIDIA’s next generation Data Center Compute Systems. We want to grow our teams with the smartest people in the world. If you're creative and autonomous, we want to hear from you! What you’ll be doing: Own and deliver OpenBMC based manageability stack for next generation Data Center Compute Systems. Own firmware delivered to data centers in terms of quality, reliability and telemetry performance. Manage and lead a distributed team of software engineers to deliver firmware stack with high quality. Work with data center architects and cloud customers for correct requirements and scope implementation to ensure speed of light product development. Work closely with cross functional teams to ensure scalable manageability architecture for all data centers products Drive efficiency, reliability and optimization in firmware architecture from a data center view point. Work closely with customers and internal teams to resolve issues at Speed of Light. What we need to see: BS, MS, or PhD in EE/CS or related field o

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role We're looking for an Engineering Manager to lead a team of highly experienced engineers building the infrastructure that powers Modal's serverless GPU platform. This is a hands-on leadership role — expect to split your time between technical contribution and people management depending on what the team needs. You'll set direction, remove blockers, and build a strong engineering culture as your team tackles hard problems in distributed computing, large-scale data handling, and performance optimization. Who You Are You're an experienced engineering leader who stays close to the work and builds alongside your team when it counts. You earn trust through technical depth, not title. You communicate clearly, help strong engineers move fast without cutting corners, and stay calm and pragmatic under pressure. You care as much about how your team gets to an answer as the answ

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Container runtimes were designed for general-purpose software workloads. AI inference is not a general-purpose workload. Running large models at production scale exposes cracks in every layer of the container stack: runtimes unaware of GPU memory constraints, images that take minutes to pull when a model needs to scale to thousands of replicas, and isolation mechanisms that weren't designed for the multi-tenant serving environments that production AI requires. The tools the industry has relied on for a decade weren't built for this, and patching around those limitations at higher layers only goes so far. Baseten owns the entire pipeline, from the moment a developer pushes a model to the moment a request gets a response. That vertical ownership means we can fix these problems at the root. The Runtime Fabrics team is doing exactly that: purpose-building the container runtime and storage layers for AI inference workloads, led by some of the world's top containerd maintainers. As Engineering Manager of the Runtime Fabrics team, you will lead this work, setting technical direction, growing a world-class team of systems engineers, and ensuring the team's output shapes not just Baseten's infrastructure but the open-source container ecosystem at large. If you've contributed to containerd, runc, or related OCI projects and are ready to lead a team solving some of the hardest problems in infrastructure today, we'd love

About the Team The ChatGPT Search Product Infrastructure team builds the foundational systems that power search experiences across ChatGPT. We develop the product infrastructure that connects models with search systems and other sources of real-time information, enabling ChatGPT to deliver timely, relevant, and trustworthy answers to users around the world. Our work sits at the intersection of product engineering, AI, and large-scale infrastructure. We build shared platforms and abstractions that enable product teams to independently develop, evaluate, and launch new search-powered experiences. These platforms provide the guardrails, testing capabilities, observability, and rollout controls needed to prevent reliability, scalability, quality, and latency regressions while supporting rapid product iteration. The team partners closely with: Post-Training on model launches, experimentation, and prompt optimization Search product verticals on new user experiences Inference on GPU efficiencies Indexing and Retrieval on the systems that identify and deliver relevant information Capacity/Fleet team to ensure optimal regionalized provisioning of GPUs and CPUs About the Role We are looking for an Engineering Manager to lead the team responsible for ChatGPT’s Search Product Infrastructure. You will set the technical and organizational direction for the systems that bring search capabilities into ChatGPT. You will guide architectural decisions across search orchestration, model and prompt integration, serving infrastructure, experimentation, observability, evaluation, and product integrations. You will balance immediate launch and product needs with the long-term reliability, scalability, latency, and maintainability of the platform. A central responsibility of this role is creating leverage for Search product verticals. You will lead the development of extensible platforms that allow those teams to independently build, test, and launch features without requiring ongoing invol