Production Support Engineer Cloud 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 As a Cloud Platform Engineer, you'll envision and build robust systems and processes that ensure our infrastructure is scalable, reliable, and efficient. This can range from automating deployments and monitoring systems to optimizing performance and managing incidents. We all work closely with our users, learning from their past struggles in operationalizing ML, onboarding them onto our platform, and turning our learnings into ideas for improving Baseten. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Infrastructure team: Multi-cloud capacity management Inference on B200 GPUs Multi-node inference Fractional H100 GPUs for efficient model serving RESPONSIBILITIES Build and maintain scalable infrastructure to support the deployment and operation of machine learning models. Establish standards and best practices for reliability and performance across the infrastructure. Automate processes when relevant, particularly for managing CI/CD pipelines. Own products and projects end-to-end, functioning as both an engineer and a project manager, with a focus on user empathy, project specification, and end-to-end execution. Collaborate with cross-functional teams to understand project requirements and translate them into technical solutions. Mentor junior team members and contribute to knowledge sharing within the organization. Navigate ambiguity and exercise good judgment on tradeoffs and

About the Role We are seeking a Cloud Infrastructure Engineer to help design and evolve the platforms that power OpenAI’s products. In this role, you will be a hands-on technical leader, driving the architecture, scalability, reliability, and security of critical infrastructure systems. You will help define how we build and operate infrastructure at the next order of magnitude, while influencing technical direction across teams. This role is both deeply technical and highly strategic, requiring strong ownership, sound judgment, and the ability to partner effectively across engineering, product, and research organizations. In this role, you will: Design and build scalable, reliable, and secure infrastructure platforms that power OpenAI products Evolve cloud infrastructure abstractions that enable rapid product development across teams Architect systems to support significant growth, performance, and operational complexity Improve server orchestration, networking, distributed systems reliability, and infrastructure security posture Influence technical direction and infrastructure strategy across multiple teams Partner closely with product, research, and engineering teams to align infrastructure with evolving needs Own operational excellence, including participation in on-call rotations, incident response, and production readiness Mentor engineers and raise the overall technical bar of the organization Contribute to a culture of high ownership, low ego, and thoughtful collaboration You might thrive in this role if you: 8+ years of experience building and operating large-scale infrastructure systems Deep expertise in Kubernetes and container orchestration at scale Strong experience designing cloud abstractions and platform infrastructure (AWS, GCP, Azure, or similar) Proven track record of leading complex technical initiatives across teams Experience operating highly reliable, secure, and scalable distributed systems Security engineering experience or security backgroun

About the Team We’re hiring a Developer Productivity engineer to support OpenAI’s Inference Runtime teams. These teams own the systems responsible for serving models reliably, efficiently, and safely across Codex, ChatGPT, API, and internal research workloads. We’re hiring a Developer Productivity Engineer to help scale the engineering systems, safeguards, and developer workflows that enable our teams to move quickly without compromising reliability or performance. This role sits at the intersection of developer experience, CI/CD infrastructure, release engineering, production readiness, and inference systems reliability. You’ll work on the tooling and operational foundations that support model launches, inference optimizations, cloud provider integrations, and large-scale deployments across a rapidly evolving inference stack. About the Role We’re looking for an autonomous, high-ownership engineer who cares deeply about making other engineers faster, safer, and more confident. A major focus of this role will be improving the tooling and infrastructure around deploy gates for inference engine images. These systems help ensure that every image released to production and research is correct, numerically sound, free of regressions, and performant across key metrics like time-to-first-token (TTFT) and time-between-tokens (TBT). You’ll help harden the systems that catch issues before they reach production, reduce noise from flaky or infrastructure-related test failures, and improve automation around triage, ownership, debugging, and escalation when failures occur. You’ll also work on improving observability, rollout safety, release automation, and developer self-service tooling across a rapidly evolving inference stack. This is not generic internal tools work. The systems you build directly impact OpenAI’s ability to support new model launches, safely ship inference optimizations to the world, onboard new infrastructure providers, and operate one of the largest and most p

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? Are you energized by building high-performance, scalable and reliable machine learning systems? Do you want to help define and build the next generation of AI platforms powering advanced NLP applications? We are looking for Members of Technical Staff to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will work closely with many teams to deploy optimized NLP models to production in low latency, high throughput, and high availability environments. You will also get the opportunity to interface with customers and create customized deployments to meet their specific needs. You may be a good fit if you have: 5+ years of engineering experience running production infrastructure at a large scale Experience designing large, highly available distributed systems with Kubernetes, and GPU workloads on those clusters Experience with Kubernetes dev and production coding and support Experience with GCP, Azure, AWS, OCI, multi-cloud on-prem / hybrid serving Experienc

About the Team The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. You’ll join the team responsible for running the core infrastructure that supports products like ChatGPT and the API. The systems we support include our kubernetes clusters, infrastructure deployment, our networking stack, cloud abstractions, and more. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role The cloud infrastructure team builds and maintains infrastructure abstractions allowing OpenAI to ship products quickly and scalably. This role is based in San Francisco, CA. In this role, you will: Design and build the development and production platforms that power our products, enabling reliability and security at scale Ensure our infrastructure can scale to the next order of magnitude Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed. You might thrive in this role if you: Have 5+ years building core infrastructure Have experience operating orchestration systems such as Kubernetes at scale Have experience building abstractions over cloud platforms Take pride in building and operating scalable, reliable, secure systems Are comfortable with ambiguity and rapid change This role is exclusively based in our San Francisco HQ. We offer relocation assistance to new employees. 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 depl

About the Team Security is foundational to OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security organization protects OpenAI’s technology, people, and products by building and operating deeply technical systems that must work reliably at massive scale. Our work underpins OpenAI’s commitments around safety, privacy, and security across research, products, and emerging platforms. The Host Assurance team exists to make bare metal and VMs dependable & scalable foundations for OpenAI: secure by default, verifiable in practice, and resilient across providers and operating models. We operate at the trust boundary between hardware and cloud-scale orchestration, ensuring that hosts are eligible to safely run workloads with predictable security properties and auditability. About the Role OpenAI is seeking a Software Engineer, Host Assurance to build and operate the services, APIs, and host software that establish and maintain trust in our compute infrastructure. You will own production software from design and implementation through testing, rollout, observability, and operation. Your work will support capabilities such as machine identity, certificate issuance and enrollment, secure bootstrap, and host attestation across bare-metal and VM environments. Success in this role requires strong technical judgment, the ability to reason across software and host-system boundaries and learn unfamiliar parts of the stack, and a practical mindset for building systems that are secure, reliable, and usable in fast-moving production environments. The systems you build will sit on the critical path of OpenAI’s frontier infrastructure investments and will directly shape how large amounts of compute are brought online - securely, responsibly, and at global scale - underpinning long-lived commitments around privacy, security, and reliability. You will partner closely with infrastructure, research, and confidential computing initiatives—inc

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 builds AI infrastructure products that developers love. That's how we grew so quickly, and why word of mouth remains one of our most important channels today. In this role, you will primarily create and distribute technical content that is unique, educational, and practical. This content will be the first Modal touchpoint for many of our users. We want to not only showcase the power and developer experience of Modal, but also serve as a trusted resource for them when implementing new AI technologies. In this role, you will: Distill the latest advancements in AI technology and educate developers on how to incorporate them. Give demos/talks about Modal and adjacent tools at developer events. Engage with users in our community, both online (X, LinkedInReddit, Slack) and at in-person events. Build relationships, integrations, and joint marketing activities with o

About the Team OpenAI’s Infrastructure Operations team is responsible for the availability, reliability, and operational excellence of one of the world’s largest AI infrastructure networks. The team owns day-to-day operations of production AI networks across Industrial Compute's data centers, working with colocation providers, deployment teams, and hardware vendors to deliver highly available GPU infrastructure for AI training and inference workloads. About the Role We are seeking an Infrastructure Operations Engineer to operate and improve the large-scale Ethernet fabrics that support GPU clusters, storage systems, and management infrastructure. This role combines hands-on production operations with automation, observability, and incident response across a global AI network. The ideal candidate has experience operating high-availability data center, cloud, AI, or HPC networks and can move comfortably from physical-layer troubleshooting to routing and fabric behavior, change execution, and root-cause analysis. You will partner closely with network architecture, systems engineering, GPU engineering, storage engineering, security, deployment, site operations, service providers, colocation partners, and hardware vendors to raise reliability and reduce operational toil. Key Responsibilities Own the operational health, availability, and reliability of production AI network infrastructure across Industrial Compute's data centers. Monitor, troubleshoot, and resolve network incidents while meeting service-level objectives (SLOs), reducing Mean Time to Detect (MTTD), and minimizing Mean Time to Recovery (MTTR). Operate and maintain large-scale Ethernet fabrics supporting GPU compute, storage, and management networks. Execute production network changes, maintenance windows, and capacity expansions with minimal customer impact. Manage the hardware lifecycle, including switch and optics replacements, RMA coordination, software upgrades, and preventive maintenance. Support new A

About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in cloud-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including cloud-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re looking for a backend engineer who can quickly understand OpenAI’s models, products, and systems, then adapt first-party deployments for other cloud platforms. You’ll build backend services, APIs, SDK integrations, authentication flows, and cloud service infrastructure that let developers use OpenAI capabilities in the cloud environments where they already build. This role involves working across teams, sometimes embedded with partner product groups, to ship products quickly and across multiple platforms at the same time. It’s a strong fit for engineers who have built developer tools, especially AI-powered tools, communicate clearly across technical boundaries, and can shape architectures that support different deployment models; experience building cloud services is a strong plus. In this role, you will: Build backend and infrastructure systems that extend OpenAI’s API platform into cloud-native environments, like AWS. Design and ship cloud-contained products that allow customers to use OpenAI capabilities while keeping workloads and data within cloud environments. Help stand up cloud-hosted Codex experiences powered by the OpenAI Responses API. Build the infrastructure and runtime abstractions

About the team The AI Deployment Engineering team is responsible for helping developers and enterprises safely and effectively deploy OpenAI technologies in production. We act as trusted technical advisors and thought partners for customers, working side by side with their teams to identify high-value use cases, design practical architectures, and move from prototype to durable deployment. Cybersecurity is one of the most urgent domains where AI can help. Security teams are under pressure to reason across code, logs, infrastructure, tickets, alerts, and vulnerability data faster than ever. As frontier models become more capable, organizations need deep technical guidance on how to evaluate, validate, and safely deploy AI systems in security-critical workflows. About the role We are looking for a Cyber AI Deployment Engineer to partner with customers and help them apply OpenAI models, APIs, Codex, and agentic workflows to real cybersecurity use cases. You will work with CISOs, security executives, application security leaders, SOC teams, security engineering teams, and hands-on practitioners to identify where AI can create measurable security outcomes. This is a customer-facing technical role for someone who can move fluidly between executive strategy, practitioner-level cyber depth, and hands-on solution design. You will help customers evaluate and deploy workflows such as secure code review, vulnerability triage, threat modeling, remediation, SOC and incident response workflows, detection engineering, cloud security, GRC automation, and security validation. You will collaborate closely with Sales, Solutions Engineering, Product, Engineering, Research, and Security to turn customer needs into safe deployment patterns, reusable field assets, and product feedback. This role is based in our San Francisco HQ. We offer relocation support to new employees. In this role, you will: Deeply embed with strategic customers as the technical lead for AI-enabled cybersecurity work

About the Team The Storage Infrastructure team builds and operates the storage foundation behind OpenAI’s most demanding workloads. We work directly with research to design storage systems for rapidly evolving experiments, while also powering production at scale. We own the platform end to end: backend systems, user-facing services and APIs, and the control planes that manage how data is placed, moved, and retained over time. Our stack spans cloud and in-house object stores across very different workload profiles, from GPU-attached systems to dedicated storage hardware. We also build the federation layer that unifies these backends behind a simple interface and routes each workload to the right storage solution. About the Role You will help build the storage platform that powers OpenAI’s research and production systems. This is a hands-on infrastructure role for engineers who want to work on deeply technical systems at scale and own them in production. You’ll work across object storage, cross-region data movement, lifecycle management, and the federation layer that provides a unified interface across multiple backends. Much of our stack runs on Kubernetes, and we primarily build services in Rust. In this role, you will: Build and operate storage services that underpin OpenAI’s research infrastructure Develop object storage systems across cloud and in-house environments Build systems for cross-region data movement, replication, and recovery Design lifecycle management capabilities that keep data durable, available, and cost-effective Evolve the federation layer that unifies multiple backend systems behind a simple interface Improve performance, reliability, and operational excellence across the platform Collaborate closely with researchers and infrastructure teams to support rapidly evolving workloads You might thrive in this role if you: Have experience building or operating distributed systems in production Have worked on storage infrastructure, object stores, dist

About the Team OpenAI, in close collaboration with our capital partners, is building the world’s most advanced AI infrastructure ecosystem. Our Industrial Compute organization develops and deploys large-scale AI campuses designed to support the next generation of frontier model training and inference workloads. The Hardware Operations team is responsible for ensuring the reliability, availability, and lifecycle health of OpenAI’s compute infrastructure. We partner closely with Data Center Operations, Fleet Health Engineering, Manufacturing, Network Infrastructure, Capacity Planning, and our infrastructure partners to maintain world-class operational performance across rapidly expanding AI environments. As we scale globally, we are building the operational frameworks, reliability standards, and sustaining engineering practices required to support thousands of GPUs and servers across multiple campuses. About the Role We are seeking a Datacenter Hardware Technician Lead to serve as the senior on-site technical authority for hardware reliability and fleet health at one of OpenAI’s flagship AI campuses. This role operates at the intersection of hardware operations, sustaining engineering, and fleet reliability. You will partner closely with Cloud Service Provider operations teams, OpenAI fleet-health engineers, hardware engineering teams, and OEM vendors to identify, diagnose, and resolve hardware issues affecting production systems. Beyond day-to-day operational support, you will drive root cause investigations, reliability improvement initiatives, lifecycle management programs, and operational readiness efforts. You will help establish hardware maintenance standards, operational procedures, and best practices that scale across future OpenAI infrastructure deployments. The ideal candidate combines deep hands-on datacenter hardware expertise with strong troubleshooting, failure analysis, and cross-functional leadership skills. Candidates must be able to sit onsite at our

About the Team The Consumer Devices team at OpenAI builds end-to-end hardware and software systems that bring AI into the physical world. We work at the intersection of custom silicon, embedded systems, operating systems, cloud services, mechanical engineering, electrical engineering, and product design to deliver reliable, production-ready devices at scale. Within Consumer Devices, Hardware Engineering eXperience, or HEX, is a new bootstrapped team building the environments, applications, compute, product-data systems, and workflows that let hardware engineers do their work without needing to troubleshoot the machinery underneath. HEX owns virtual engineering environments, HPC/GPU compute, storage, networking, licensing, MCAD/ECAD/CAE applications, PLM, product data, automation, validation, and support as one connected system. About the Role As a Staff PLM & Engineering Applications Engineer, you will be one of the first technical builders of HEX and the primary counterpart to the HEX lead. You will own the engineering-application and product-data side of the hardware engineering experience, with an initial focus on NX, Teamcenter, licensing, parts import, integrations, packaging, validation, and user workflows. This is not a traditional Teamcenter administration role and not a Corporate IT application-support role. You will take complex, fragile workflows and turn them into reliable engineering systems. This role is highly hands-on and systems-oriented. You will not inherit a mature environment and support queue. You will help build a fresh one, replacing manual setup guides, tribal knowledge, repeated support issues, and team handoffs with tested automation and reliable workflows. In This Role, You Will Own the technical architecture, deployment, configuration, integration, validation, and long-term operation of NX and Teamcenter. Build reliable workflows for parts import, product-data migration, metadata quality, BOMs, revisions, lifecycle states, and releas

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 As an Infrastructure Software Engineer at Baseten, you'll build and maintain components of our ML inference platform that powers production AI applications. You'll contribute to the core infrastructure, enabling developers to deploy, scale, and monitor ML models with high performance. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Infrastructure team: Multi-cloud capacity management Inference on B200 GPUs Multi-node inference Fractional H100 GPUs for efficient model serving RESPONSIBILITIES Develop infrastructure components for our ML inference platform using Python and Go Implement and maintain Kubernetes deployments for model serving Contribute to our inference orchestration layer for model deployments Build and enhance monitoring systems for model performance metrics Implement efficient resource management solutions for ML workloads Support infrastructure automation to improve ML deployment workflows Work closely with team members to implement technical solutions Help balance performance optimization with system reliability Participate in technical discussions around infrastructure improvements Learn and apply infrastructure best practices REQUIREMENTS Bachelor's degree or higher in Computer Science or related field Proficient coding abilities in one or more popular programming or scripting languages; Go proficiency is a plus Working knowledge of Kubernetes and containeriza

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! This is a hybrid role that will require two days in-office each week on Tuesdays and Wednesdays at our SF location on 130 Sutter Street. About the Role Every business function at Taskrabbit — Marketing, Customer Support, Finance, Operations — is a "customer" with real workflows, real data, and real friction. Your job is to embed with them, scope their use cases, and build the Claude-powered agent, automation, or tool that solves them. This is an internal-facing role — there is no external customer or product work. Reporting to the Director of AI Strategy and Enablement, you'll operate the way an FDE operates at a high-growth AI company: full ownership of a deployment from discovery through production and direct accountability for whether what you ship actually changes a metric. In most cases you'll own a build end-to-end solo; in some functions you may partner with that team's own subject-matter expert to pair domain depth with