San Antonio Looking For Kitchen Staff Jobs

About the Team Like every team at OpenAI, the Marketing team contributes to our broader mission of ensuring responsible and widespread adoption of artificial intelligence. With that aim in mind, we are responsible for developing and executing strategies that drive awareness, engagement, and usage for OpenAI’s products and platform amongst our core audiences. Our focus extends beyond just promoting product features; we aim to provide valuable insights and resources that help our users make the most out of AI technologies. The Marketing Insights & Analytics team aims to understand the markets, audiences, behaviors, attitudes and needs to shape outreach strategies and inform product and business decisions. We’re the strategic partner that discovers insights, specifically: foundational understanding, marketing strategy, thought leadership, measurement and tracking. About the Role You will be the Market Research Lead that translates insights into actionable marketing plans and executions, drive business results, and orient the team towards strategic thinking to drive brand outcomes. This is critical as we hope to reach millions of users and businesses worldwide. This role can be based in San Francisco, CA or NYC, NY utilizing a hybrid work model (3 days per week in-office). In this role, you will: Play an integral part of Marketing and be a strategic partner to brand, product marketing, creative, product and beyond. Design, execute, and deliver high-impact research using mixed methods. Work on a diverse portfolio of business challenges - how do we reach the next billion people, how do we grow internationally, how do we position our suite of products, and how do we ship joy to our customers. Translate business questions into research plans. Translate data into clear, compelling narratives. Develop deep empathy for developers, builders, and technical decision-makers, understanding their workflows, motivations, and pain points across the lifecycle Shape go-to-market str

About the Team The Codex team is responsible for building state-of-the-art AI systems that can write code, reason about software, and act as intelligent agents for developers and non-developers alike. Our mission is to push the frontier of code generation and agentic reasoning, and deploy these capabilities in real-world products such as ChatGPT and the API, as well as in next-generation tools specifically designed for agentic coding. We operate across research, engineering, product, and infrastructure—owning the full lifecycle of experimentation, deployment, and iteration on novel coding capabilities. About the Role As a Performance & Systems Engineer on the Codex team, you will be responsible for whole-system optimization across a complex, evolving stack. Codex spans LLM inference, cloud orchestration, agentic work management, and multiple product surfaces. Your job will be to identify and land high-leverage changes—across infrastructure, modeling, and product layers—that make Codex agents significantly faster and cheaper to serve. We’re looking for generalists who thrive in ambiguity and love chasing performance bottlenecks to ground. This is a high-ownership role where your work will directly improve the experience of millions of users. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Hunt down and address inefficiencies across the Codex system stack, from agent behavior to LLM inference to container orchestration, and beyond. Build tooling to measure, profile, and optimize system performance at scale. Collaborate with researchers and engineers to land high-ROI changes that improve latency and cost. You might thrive in this role if you: Have experience operating across both ML systems and cloud infrastructure. Enjoy diving into messy, ambiguous problems and emerging with clear wins. Think holistically about performance, balancing spee

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 AWS-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 AWS-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 hiring Machine Learning Engineers to build and improve the AI systems that help strategic partners adapt OpenAI models to important use cases in cloud-native environments. This role spans post-training workflows, evaluation, data pipelines, model behavior, and API/infrastructure integration. You’ll work at the boundary between partner needs and core ML systems: helping teams understand what is and isn’t working, diagnosing issues in training and evaluation workflows, and turning those learnings into improvements to the underlying platform. You should enjoy working with external technical partners, extracting the real goal from messy requests, and pushing back or reframing when the requested experiment is not the highest-leverage path. You’ll collaborate closely with Research, Applied, Safety Systems, infrastructure teams, and external technical partners to solve ambiguous model-performance problems. When you succeed, strategic partners and internal teams will be able to improve model behavior with confidence, driving measurable product improvements while the systems behind that work become more reliable, scalable, and effective over time. In this role, you will Partner with strategic customers and in

About the team OpenAI’s mission is to build safe artificial general intelligence (AGI) which benefits all of humanity. This long-term undertaking brings the world’s best scientists, engineers, and business professionals into one lab together to accomplish this. In pursuit of this mission, our Go To Market (GTM) team is responsible for helping customers learn how to leverage and deploy our highly capable AI products across their business. The team is made of Sales, Solutions, Support, Marketing, and Partnership professionals that work together to create valuable solutions that will help bring AI to as many users as possible. About the Role Our GTM team is uniquely positioned to help customers realize the transformative potential of advanced AI models for their businesses and end users. As part of the GTM Strategy & Operations team, you’ll play a critical role in guiding the GTM strategy and driving the operational efficiency to accomplish this mission. This role serves as a trusted advisor to GTM leadership—providing data-driven insights, managing core operating cadences, and leading high-impact projects that influence how we engage with customers and scale our business. You’ll collaborate cross-functionally with Finance, Enablement, Data and Growth Strategy teams to align efforts, drive efficiencies, and accelerate growth. This role is a central role, meaning it is not tied to a specific business partner, but rather designing the global processes for the business. In this role, you'll: Design, build, and manage our operating rhythms (Forecasting, Pipeline Council, Big Deal Reviews, and MBRs/QBRs). Conduct strategic analyses to determine trends and identify opportunities for process and strategy optimization Collaborate with GTM leadership and cross-functional stakeholders to develop go-to market strategy and resource plans Lead strategic projects to improve efficiency and effectiveness across the revenue organization. Partner closely with technical teams to impl

About the Team Tax and Trade at OpenAI shapes business strategy by embedding critical tax, export control, customs, and cross-border considerations into how the company builds, sources, scales, and operates in support of the mission. We combine deep expertise with practical systems thinking to look around corners, identify emerging risks and opportunities early, and help teams make smarter decisions at the point where strategy becomes execution. Across procurement, hardware operations, manufacturing, logistics, finance, legal, supplier onboarding, and operator workflows, we build robust, scalable support services leveraging cutting-edge technology—including governed AI and automation—to make complex regulated work more durable, more efficient, and easier to scale. About the Role We’re hiring a Senior Manager, Export Controls to lead OpenAI’s export controls strategy and operating model. This is a senior role with broad scope across advanced computing, semiconductors, software, hardware, manufacturing, and high technology partnerships. You will refine how OpenAI classifies controlled technology, software, and hardware, structures access-controlled environments, manages licensing and supplier commitments, and scales export-control operations in a way that supports the company’s pace of innovation. You will also shape how OpenAI applies AI and agentic workflows to policy-heavy operational work, building systems that make complex rules easier to navigate and easier to execute. In this role, you will: Refine the strategy and operating model for OpenAI’s export controls program across advanced computing, semiconductors, software, hardware, manufacturing, and high technology partnerships. Own export classification and licensing strategy for controlled technical data, software, hardware, and research environments. Lead the design and operation of compliant controlled environments and related governance processes. Partner with Research and Infrastructure to support efficient

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 OpenAI’s Hardware organization develops system and infrastructure solutions tailored to the demands of advanced AI workloads. We work across the full stack—from silicon to system integration—partnering closely with internal teams and external vendors to define and deliver next-generation AI infrastructure. Our team focuses on defining scalable, high-performance system architectures and reference designs that balance performance, cost, and operational efficiency across rapidly evolving technologies. About the Role We are seeking a 3P Architect to define and drive rack- and cluster-level reference designs in collaboration with external partners. This role is responsible for translating workload requirements and system-level goals into concrete architectures, aligning partners on critical design attributes, and ensuring vendor roadmaps meet our infrastructure needs. You will work closely with performance modeling and internal architecture teams to evaluate tradeoffs, while owning the end-to-end definition and execution of third-party system designs. This includes identifying gaps in current technologies, driving vendor development, and shaping future infrastructure capabilities. This role requires strong system intuition, cross-functional leadership, and the ability to operate effectively across internal teams and external ecosystems. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance. Key Responsibilities Define rack- and cluster-level reference architectures for AI infrastructure deployments. Translate workload requirements into clear system design specifications and partner deliverables. Collaborate with performance modeling teams to evaluate architectural tradeoffs and system behaviors. Align internal stakeholders and external partners on critical system attributes (performance, cost, power, reliability, scalability). Identify gaps in current technology offerings and dr

About the Team The Connectivity Software Engineering team is responsible for enabling seamless, secure, and high-performance wireless connectivity across OpenAI’s products. We design and optimize Bluetooth, BLE, Wi-Fi, and emerging wireless technologies to ensure robust device pairing, network performance, and interoperability. Our work spans kernel drivers, system services, and user-level tools, with a focus on real-world performance, scalability, and reliability. About the Role OpenAI is seeking a Connectivity Software Engineer to design, implement, and optimize wireless connectivity features across our product ecosystem. You’ll work at the intersection of systems software, wireless standards, and hardware integration—building robust pairing and provisioning flows, debugging low-level protocols, and driving performance under real-world RF constraints. You will also support certification, field interoperability, and fleet-scale connectivity infrastructure. This role is based in San Francisco, CA . We use a hybrid work model of 4 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, implement, and debug Bluetooth/BLE and Wi-Fi features across kernel drivers, BlueZ/wpa_supplicant/hostapd, and systemd/D-Bus services Deliver robust pairing, bonding, and provisioning flows (GATT/GAP, LE Audio/LC3, WPA3/802.1X, captive portals, NAN) Optimize link performance: throughput, latency, jitter, roaming, coexistence (BT↔Wi-Fi), and power modes (TWT, WoWLAN) Build reliable network management using NetworkManager/nmcli, nl80211/cfg80211/mac80211, DNS/DHCP/mDNS, P2P/SoftAP Instrument and analyze with packet captures and tooling (btmon/hcidump, Wireshark, iperf, eBPF/perf, spectrum sniffers) Drive interoperability and certification readiness (Bluetooth SIG, Wi-Fi Alliance) and resolve field issues with root-cause fixes Contribute to OTA-safe configuration, telemetry, and diagnostics for fleet-scale operation You might thrive in

About the Team The Scaling team is responsible for the architectural and engineering backbone of OpenAI’s infrastructure. We design and deliver advanced systems that support the deployment and operation of cutting-edge AI models. Our work spans system software, networking, platform architecture, fleet-level monitoring, and performance optimization. About the Role We’re hiring an SW Engineer to enable production workloads and end-to-end testing on new platforms. This role will include creating new test harnesses and platform stress benchmarks, porting existing inference and training workloads to new, sometimes early-access, systems/hardware, analyzing performance and bottlenecks, and characterizing the end-to-end behavior of new systems (compute, comms, storage, control plane, and failure modes). Key Responsibilities Port and validate key inference and training workloads on new platforms/SKUs as they arrive; drive correctness, performance, and stability to an internal readiness bar. Build a suite of benchmarks and stress tests that capture real E2E behavior of our workloads by exercising all aspects of a system, including CPU, GPU, memory subsystem, frontend, scale-up, and scale-out networking (including WAN traffic, NVlink and RDMA collectives), storage, thermals, and any other relevant parts. Deep-dive performance on distributed training/inference: Collective performance and tuning (across NCCL/RCCL and internal libraries) Overlap of compute/communication, kernel-level bottlenecks, memory bandwidth and scheduling effects Create repeatable test harnesses that run in CI / lab environments and produce actionable outputs (pass/fail, performance score, regression detection). Partner with systems + fleet bring-up engineers to ensure the platform is not only stable and performant, but also operationally usable and scalable (containerization, K8s integration, telemetry hooks, failure triage loops). Work cross-functionally with vendors and internal stakeholders by producing

About The Team Our mission is to bring OpenAI products to life for every customer. Demo Experience equips customer-facing teams with the experiences, systems, and confidence to make frontier capabilities tangible, relevant, and trustworthy. OpenAI’s products and customer needs are evolving rapidly. Demo Experience closes the gap between a frontier capability and a credible customer experience—making new capabilities understandable, demonstrable, and reusable quickly at scale. Working across Product, Engineering, Marketing, Operations, and GTM, we turn recurring customer needs into reusable capabilities and raise the standard for every customer conversation. About The Role Demo Experience Engineers work at the intersection of product engineering, technical storytelling, and GTM execution. You will own ambiguous, high-leverage problems end to end—from building agentic prototypes to creating the infrastructure and self-service tools that make them reliable and reusable. Your work will help customer-facing teams move faster, reduce avoidable failures, and translate frontier product capabilities into clear customer value. You will also turn recurring patterns from customer-facing work into product feedback, launch-readiness improvements, and scalable systems. Success in this role means teams can demonstrate new capabilities sooner and with greater confidence. Recurring requests become reusable capabilities instead of one-off work. Demo experiences are accurate, reliable, and safe. Insights from customer-facing work improve product and readiness decisions. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In This Role, You Will Own end-to-end demo readiness for new and priority product capabilities, including environments, integrations, synthetic data, evaluations, reliability checks, and fallback paths. Build compelling prototypes, LLM agents, and reference flows that mak

About the Team OpenAI’s mission is to ensure that artificial general intelligence benefits all of humanity. A majority of our users interact with our products in languages other than English, and our products must work seamlessly across languages, regions, and cultures. The Internationalization team builds the infrastructure that enables OpenAI products to ship globally by default. We develop the systems that power localization, international product launches, and high-quality global user experiences across all OpenAI products. About the Role As a Senior Software Engineer on the Internationalization team, you will build the systems that power localization and international product launches at OpenAI. You’ll work on the platform that manages product content, translation workflows, and localization infrastructure across our products. This role sits at the intersection of AI systems, developer platforms, and product infrastructure. In this role, you will Build and scale OpenAI’s localization, content, and experimentation platform used across OpenAI product teams, including open-source components: Develop AI-powered translation pipelines combined with human-in-the-loop review workflows. Design systems that reliably deliver localized product content across web and mobile apps. Build tools that enable linguists and localization teams to review and improve translations. Develop developer tooling that simplifies localization and internationalization workflows. Build and maintain internationalization libraries used across OpenAI products: Design systems that correctly handle numbers, currencies, dates, and pluralization across locales. Improve support for multilingual interfaces and right-to-left languages. Partner with product teams to improve the international readiness of new features. You might thrive in this role if you Have strong software engineering experience building backend or full-stack systems. Have familiarity with Java, React, MySQL, and cloud infrastructure p

About the Team The Platform Analytics team builds the systems OpenAI researchers use to understand the quality and behavior of the models we train including what models are doing, why they behave in a particular way, and how that behavior changes across experiments. Neptune is a core part of this work. It ingests, stores, queries, and visualizes large volumes of metrics from pretraining, post-training, and reinforcement learning. Hundreds of researchers depend on these systems in their daily work to compare experiments, debug unexpected behavior, and decide what to try next. Our scope is broader than metrics. We also build platforms that help researchers analyze samples, traces, evaluation results, and other structured or unstructured data through dashboards, APIs, and increasingly agent-driven workflows. These systems need to remain fast, reliable, and understandable as the scale and complexity of research change quickly. We are not trying to become a consulting team that builds a separate solution for every research project. We work directly with researchers to understand recurring problems, then turn them into reusable infrastructure and platform capabilities that many teams can build on. About the Role We’re looking for a hands-on experienced software engineer who can take ownership of a critical system and drive it from problem definition through production adoption. This person should be able to own a platform such as CacheHouse end to end: define its technical direction, design its data model and storage architecture, integrate it with several research dashboards and workflows, guide one or two engineers, and ensure the system works reliably for its users. The right candidate should already bring the technical judgment, ownership, and execution expected at this level. The primary learning curve should be OpenAI’s stack and research problem space, not learning how to lead a complex engineering effort or deliver a production system. You will work directly with

About the Team The Personalization-Memory team, within OpenAI's broader Personal AGI organization, is focused on developing agents that can learn from prior interactions in order to become more helpful and efficient over time. We build general-purpose memory and personalization capabilities that transfer across ChatGPT and other agentic products, and we collaborate with applied engineering on the product surfaces that allow users to interact with memory. About the Role As a Research Engineer / Research Scientist on the Personalization-Memory team, your work will span memory architecture, post-training, and developing long-horizon tasks for training and evaluations. We're looking for individuals who have a background in reinforcement learning research, are able to iterate quickly, and who can convert scientific rigor and long-term research into realized product impact. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own and pursue a research agenda for improving long-horizon memory and personalization in frontier models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. Collaborate closely with the research and product teams to influence the shape of technical solutions in the product. You might thrive in this role if you: Love being on the cutting edge of RL and frontier model research. Value principled approaches and research craftsmanship. Are passionate about long-horizon tasks, memory, and turning your research into product impact. Are comfortable diving into a large ML codebase to debug. Thrive in a fast-paced, dynamic, and technically complex environment. 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 syst

About the Team The Agent Enablement team works across engineering, product, design, and research to bring our technology to the world. We seek to learn from deployment and broadly distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. We aim to make our innovative tools globally accessible, transcending geographic, economic, and platform barriers. Our commitment is to facilitate the use of AI to enhance lives, supported by rigorous insights into how people use our products. About the Role We are looking for experienced full-stack engineers to join our new Agent Enablement team. Our goal is to design and grow an open ecosystem of agent-enabled sites and services. This is a wide-ranging role: you’ll build new user and agent identity protocols, user experiences to control and observe agents across web, desktop, and mobile, and much more. We will rely on you to drive our technical decisions while also steering our product and partnership direction, optimizing for both short-term impact and long-term success of the ecosystem. We value engineers who are impact-driven, autonomous, and adept at removing barriers to forward progress. In this role, you will: Design the primitives and protocols for an open agent ecosystem, enabling our users’ agents to make the best use of sites and services across the internet. Build a next-generation user experience to observe and control agents, across web, desktop, and mobile. Evolve our approach to token consumption across subscriptions and API customers. Execute on fast-paced projects in collaboration with research, design, data science and other product engineering teams. Work closely with our strategic customers and partners to grow the ecosystem. You might thrive in this role if you: Have strong full-stack engineering skills and experience shipping customer-facing products from concept to production. You’re comfortable working across frontend, backend, APIs, data models, and product desig

About the Team The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time. About the Role We’re looking for engineers to build the infrastructure that powers Codex agents in production. This role focuses on the systems that let models safely execute code, interact with tools, complete long-running tasks, and operate reliably and efficiently at scale. You’ll design and operate the infrastructure behind sandboxed execution, orchestration, stateful workflows, app-server and SDK boundaries, and model rollouts. You’ll work at the intersection of distributed systems, developer tooling, and AI, building primitives that make Codex faster, safer, more reliable, and easier for the rest of the organization to build on. What You’ll Do Design and build execution environments for AI agents, including sandboxing, isolation, and reproducibility. Develop systems for agent orchestration across multi-step, tool-using workflows. Build infrastructure for running, testing, and debugging code generated by models. Create state and memory systems that allow agents to persist context across long-running tasks. Optimize tokens, latency, reliability, and cost across Codex’s production fleet. Support model rollouts, capacity planning, and the core tradeoffs between quality, speed, and economics to manage a fleet of frontier agents at scale. Build shared platform capabilities that unblock product teams, partner teams, and open source Codex. Yo