Compute Strategy And Transactions in San Francisco

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 We’re seeking a GPU Kernel Engineer to join our team at the cutting edge of AI acceleration, where your code directly impacts the performance of state-of-the-art machine learning models. As a GPU Kernel Engineer, you'll craft the foundation that powers modern AI workloads, optimizing every microsecond of computation to enable breakthrough applications. You'll work in a fast-paced, intellectually stimulating environment where technical excellence is paramount and your contributions directly influence production systems serving millions of users across numerous products. This role offers exceptional growth potential for engineers passionate about low-level optimization and high-impact systems work. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Model Performance team: Baseten Embeddings Inference: The fastest embeddings solution available The Baseten Inference Stack Driving model performance optimization RESPONSIBILITIES Core Engineering Responsibilities Design and implement high-performance GPU kernels for key ML operations, including matrix multiplications, attention mechanisms, and mixture-of-experts routing Write and optimize code using CUDA, PTX assembly, and architecture-specific techniques Apply advanced performance optimization methods such as memory coalescing, warp-level programming, tensor core acceleration, and compute/memory overlap Performance & Innovation Impl

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: Modal is the cloud platform built for AI. We're used by the world's leading AI labs, startups, and researchers to run compute-intensive workloads: training runs, inference, sandboxed code execution, and more. We're hiring a Community Manager in SF to make Modal a fixture in the AI developer community. You'll bring developers together through meetups, hackathons, and events of our own, and build the kind of community that keeps showing up. You know how to rinse and repeat the process, but always with a creative bend. In this role, you will: Co-host developer meetups with partners in our ecosystem. Find the right speakers, build the relationships, and run the events together. Prior examples: High Performance Inference for Open LLMs , Voice AI Builders Night , RL with Modal and Prime Intellect , FDE Happy Hour . Sponsor hackathons that attract highly technical enginee

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. ABOUT BASE LABS Base Labs is a research lab pushing the frontier of open-source LLMs. We think intelligence should be democratized, not controlled by a handful of closed labs and we think very few teams are actually positioned to do something about that. Backed by Baseten's training and inference infrastructure, we have the compute, resources, and talent to take on hard problems at the frontier and open-source what we learn along the way. Our mission is to help build a world where intelligence isn't concentrated, but spread across an ecosystem of models that anyone can build on. That mission shapes what we choose to work on, how we work on it, and who we want in the room. We are accepting applications on a rolling basis for our first cohort of Base Labs Fellows, which is expected to start in late September. Apply using this link. BASE LABS FELLOWSHIP OVERVIEW The Base Labs Fellowship is designed to give researchers exposure to what frontier research looks like in industry. We provide funding, mentorship, and full support to our fellows, with the goal of producing rigorous, published research that shapes both the open-source ecosystem and Baseten's technical roadmap. We run multiple cohorts of Fellows each year and review applications on a rolling basis. This application is for cohorts starting in Sept 2026 and beyond. WHAT TO EXPECT 3 months of full-time research from our San Francisco office A dedicated 1:1 mentorship

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 OPPORTUNITY We are looking for Senior Software Engineers to join our team. This is a specialized, high-impact role sitting at the intersection of high-performance computing (HPC) and Large Language Model (LLM) engineering. You will not just be building the automated "speedometer and diagnostic" suite for our next-generation AI infrastructure; you will be defining the roadmap, driving key technical decisions, and taking full ownership of the future of this work. RESPONSIBILITIES Benchmarking : Evaluate, run and automate standard LLM quality benchmarks (GSM8K, MMLU) alongside custom performance suites for specific workloads (e.g., long-context window, KV cache reuse, disaggregated serving). DevEx Improvement : Develop and maintain internal GPU-enabled development environments (similar to GitHub Codespaces). You will ensure the team has seamless, high-performance "dev machines" optimized for model experimentation. Tool Development : Build and contribute to open-source tools such as InferenceMAX and genai-bench to automate model evaluation, benchmarking and analysis. System Profiling : Use profilers like PyTorch Profiler, NVIDIA Nsight Systems and py-spy to collect performance profiles, identify bottlenecks, and debug the compute/networking stack. Monitoring & Observability : Develop real-time dashboards and alerts to monitor system health, model startup times, and runtime performance. Continuous Integration : Auto

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 We’re looking for a customer-obsessed software engineer to come ship with us. You’ll own features like multi-node training and products like serverless reinforcement learning (RL) from conception to MVP (and from MVP to GA!). You’ll work through the stack, architecting solutions from API and UI down to our infrastructure layer. You’ll fine tune models yourself to develop an understanding of user workflows. You’ll work closely with research engineers leveraging state-of-the-art training techniques to build experiences that accelerate model development and solve for real pain points. If you’re excited to dive deep into the training, let’s talk! THE PRODUCT Take a look at what we’ve built so far: Overview of the product so far Training docs overview Story of the Training product Research we've done EXAMPLE INITIATIVES Checkpointing Pipeline: Our checkpointing pipeline starts with automated checkpointing, a feature that ensures that versions of models created during training are automatically backed up to the cloud. Users are able to then deploy checkpoints seamlessly into inference servers, providing point-and-click integrations into inference frameworks like vLLM and Baseten’s Inference Stack. This enables customers to quickly evaluate the performance of their checkpoints with real traffic. Multinode training: Multinode training enables customers to easily run training jobs across multiple compute nodes, enablin

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. At Baseten, we are building the global operating system for distributed, heterogeneous AI hardware. We believe that as LLM and multi-modal workloads scale, the network is the computer. We are looking for foundational engineers to lead our GPU Networking efforts, making RDMA a first-class building block in our infrastructure and unlocking the next generation of distributed inference optimizations. THE OPPORTUNITY Networking and compute are no longer separate disciplines; they are converging. The massive throughput of H100, B200, and NVL72 architectures enables and demands a new approach where communication is co-optimized alongside computation. We are entering an era where the network is an active accelerator, leveraging smart hardware offloads and direct interconnects to ensure that data movement operates at wire-speed. In this role, you will go beyond network configuration to architect the software fabric that unifies thousands of GPUs into a cohesive operating system. While you will leverage the best of the open-source ecosystem, you won't be limited by it. Where off-the-shelf solutions stop, you will build from scratch, engineering the primitives required to co-optimize communication and compute for Disaggregated Serving, Wide Expert Parallelism (WideEP), and lightening cold starts. WHAT YOU'LL DO Make RDMA First-Class: You will work on integrating RDMA/RoCE/InfiniBand capabilities directly into our inference stack,

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 role? At Cohere, we believe in the power of multimodal AI to revolutionise the way we interact with technology. Our engineering teams push the boundaries of what's possible, and we're looking for talented individuals to join us on this exciting journey. With an exceptional ratio of compute resources to engineers, we provide an ideal environment for you to explore, innovate and shape the future of AI. July 31st 2025 - Cohere's Multimodal team Introduced Command A Vision: Multimodal AI Built for Business. At release our new flagship vision-language model: ● Consistently outperforms major models like Llama 4 Maverick, Mistral Medium/Pixtral Large, and GPT4.1 ● 83.1% average benchmark (73.5% MathVista, 90.9% ChartQA...) ● Built for the real world - 112B parameters running on just 2 GPUs ● Open weights live on HuggingFace With a focused team, breakthrough performance doesn't require breakthrough compute. Focus on the things that matter, and join the team. As a Member of Technical Staff with a focus on Multimodal AI, you will: Design and develop cutting-edge multimodal AI systems, integrating various modalities such as text,

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

What you’ll do Design and implement secure cloud pipelines that ingest very large scan datasets (multi-terabyte), reliably and resumably. Build orchestration for GPU-accelerated reconstruction and analysis with strong retry semantics, idempotency, and cost controls. Define end-to-end data lifecycle for medical imaging: raw vs intermediate vs derived artifacts, retention policies, and reproducibility. Implement security + compliance primitives appropriate for HIPAA/PHI: encryption in transit/at rest, key management, least privilege, audit logs, and access reviews. Build operational tooling: monitoring, alerting, runbooks, and incident-driven improvements for a growing device fleet. What we’re looking for Strong experience with cloud batch/queueing/orchestration, storage systems, and data pipeline reliability. Experience shipping production systems that handle large data volumes and failure-prone networks. Practical security mindset (least privilege, secrets, audit logging) and comfort operating in compliance-constrained environments. Useful experience Building reliable data pipelines at scale (queues/orchestration, resumable uploads, GPU batch execution) with strong observability. Security + privacy by default: encryption, least-privilege access, auditing, and practical HIPAA/PHI guardrails. Owning the “boring” backend details that keep a lean team moving: schemas/migrations, cost controls, retries, and runbooks. Understanding compute tradeoffs across hardware options, and specifying appropriate cloud resources.

About Flexport: At Flexport, we believe global trade can move the human race forward. That’s why it’s our mission to make global commerce so easy there will be more of it. We’re shaping the future of a $10T industry with solutions powered by innovative technology and exceptional people. Today, companies of all sizes—from emerging brands to Fortune 500s—use Flexport technology to move more than $19B of merchandise across 112 countries a year. The recent global supply chain crisis has put Flexport center stage as we continue to play a pivotal role in how goods move around the world. We are proud to have the support of the best investors in the game who believe in our mission, solutions and people. Ready to tackle global challenges that impact business, society, and the environment? Come join us. Help Win New Business The Opportunity: We are scaling our dedicated Data Center practice, and we are looking for the person who will lead it. This is a founding commercial role. You will start as a team of one, owning the full sales motion end-to-end, and you will build the team around you as the practice grows. You will define how Flexport goes to market with hyperscalers, hardware OEMs, and the broader ecosystem. You will set the playbook, win the first marquee accounts, and hire the people who scale what you build. Reporting directly to the Regional General Manager, you will operate with a high degree of autonomy and direct access to executive leadership. This role features a 50/50 compensation model (Base + Uncapped bonus, with accelerators), with OTEs of $350k+, designed for strong leaders who take bets on themselves. Why This Role Is Different: The data center logistics market is not a standard freight problem. A single AI compute rack can cost more than $1 million and weigh up to 4,000 pounds. Racks contain Class 9 dangerous goods (lithium-ion batteries) and liquid cooling systems requiring specialized handling. Construction sequencing failures delayed 57% o

About the Team This team builds and operates the systems that enable OpenAI researchers to run reliable, scalable, and efficient research workflows. The team sits close to research and works across infrastructure, systems, and automation to make sure researchers have the tools and environments they need to move quickly. The work spans software engineering, infrastructure, systems administration, cluster operations, and reliability engineering. As OpenAI’s infrastructure evolves from bespoke bare-metal systems toward more standard, scalable platforms, the team needs engineers who can understand how systems work end-to-end and build the right abstractions without reinventing the wheel. About the Role As a Software Engineer on this team, you will build and operate the infrastructure that supports frontier research and critical research-facing systems. You will work on systems that sit close to the metal, but the role is not limited to classic operations or sysadmin work. We are looking for someone who can reason about networking, bootstrapping, Kubernetes, scalability, automation, and reliability - while also writing software to make these systems better over time. This role is a strong fit for an independent, high-ownership engineer who enjoys reliability-heavy infrastructure work but still wants to build. You do not need to come in as a kernel expert or highly algorithmic optimization engineer, but you should be deeply curious about infrastructure, comfortable debugging complex systems, and excited to support researchers doing novel work. We expect you to: Build and operate reliable infrastructure for research workloads and research-facing services. Support and improve systems across data infrastructure, processing, crawl and ingest, caching, search, observability, and clusterwide services. Improve cluster bootstrapping, provisioning, automation, and deployment workflows. Debug issues across networking, compute, storage, orchestration, and service reliability layers.

About the Team OpenAI's research training infrastructure powers how our frontier models are trained and evaluated. The Simulation team sits at the intersection between the agentic harness that powers OpenAI's products and the research infrastructure where GPT-next is trained, ensuring that our model's training environment is as realistic as possible. This team owns the integration layer that connects our production harness capabilities into the training stack. The work is highly cross-functional and high leverage: researchers depend on it to run experiments and evaluations reliably as well as to develop the next generation of harness capabilities. Failures in this surface can materially affect training velocity and correctness. About the Role We're looking for a Principal Software Engineer to lead the architecture and evolution of the Simulation Platform. You'll own a critical interface between research and engineering, building the systems, APIs, and operational patterns that let researchers use agentic coding infrastructure safely and effectively in training environments. This role is ideal for a senior backend or infrastructure engineer with strong technical judgment, product sense for highly technical users, and the ability to drive execution across multiple teams. The highest-leverage work is building robust infrastructure that supports and accelerates research without compromising engineering quality. In this role, you will Design, build, and evolve the integration between the Codex harness that powers OpenAI's products and research training infrastructure used for training GPT-next Build a platform for our LLMs to train and be evaluated in simulated environments that mimic their deployment setting as closely as possible, on every axis: agentic harness, compute substrate, timing, tools, data sources, humans in the loop, and more Own major integration surfaces end-to-end, from architecture and API design through rollout, operations, and long-term maintenance Bu

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role We believe that the final enabler for AGI is spending compute on context. As a Context Researcher on Agent Post-Training, you will scale compute spent on context. You will get to work in our frontier training stack on enabling the next paradigm of model training with a clear product interface for iterative deployment (Codex Chronicle). You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might Design and run experiments that improve scaling of compute on context. Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. Build evals and environments that expose the next set of model failures,

About the Team The Agent Infrastructure team at OpenAI is responsible for building systems that enable training and deployment of highly useful AI agents, both internally and for the world. We work hand-in-hand with researchers to design and scale the environment in which agentic models are trained – providing a workspace for AI models to execute code, debug issues, and develop software just as human SWEs do. Our training environment for agentic models operates at an extremely high scale and has the flexibility to emulate any environment in which an agent might work. At the same time, our team builds and maintains OpenAI’s core platform for the deployment and execution of agents in production. Our systems power products such as Codex, Operator, tool use in ChatGPT, and future agentic products. Some of the most challenging technical problems in scaling the capabilities and utility of agents and agentic models lie in the infrastructure layer – and our team is focused on building the research and production systems that enable OpenAI to train the most capable models in the world, and maximize the utility of our agentic products for users around the world. About the Role As a Software Engineer on the Agent Infrastructure team, you will have the opportunity to work closely with both research and product at OpenAI - building and scaling systems to train highly capable agentic models, and building the platform and integrations to launch new agents to hundreds of millions of users worldwide. Your work will consist of both building new capabilities - standing up the infrastructure and integrations needed to train more complex agentic models - and rapidly scaling these new capabilities to some of the largest compute clusters in the world. At the same time, you’ll be instrumental to the launch of agentic products at OpenAI - building, maintaining, and scaling the production platform on which all agents run. We’re looking for people with deep experience building AI infrastructu

About the Team OpenAI’s Applications Engineering organization builds and operates the products (such as ChatGPT & Codex) that bring our cutting-edge research to millions of users and developers worldwide. The Applied Foundations team owns the core product and platform layers that make those experiences possible — from identity & access, to safety to payments & commerce across all of our apps. Our teams span product engineering, infrastructure, and safety, working together to deliver technology that is reliable, secure, and trusted at global scale. About the Role We’re hiring Backend Software Engineers to design and implement safe services and infrastructure that power our core products. What You’ll Do Architect, build, and improve scalable backend systems and APIs. Drive performance, reliability, and safety across distributed services. Implement data storage, retrieval, compute, and integration solutions. Participate in long-term architectural planning and technical design reviews. Collaborate with cross-functional teams to design solutions that protect against and mitigate adversarial attacks without compromising user experience. You Might Thrive Here If You: Have strong experience with distributed systems, APIs, and backend languages (e.g., Go, Python, Rust, C++). Have experience setting up and maintaining production backend services and data pipelines. Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed. Enjoy building resilient services that handle large scale and complexity. Are self-directed and enjoy figuring out the best way to solve a particular problem Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done. 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