Human Resources Operations Specialist in San Francisco

About the Team The Workload Networking team is responsible for the collective communication stack used in our largest training jobs. Using a combination of C++ and CUDA we work on novel collective communication techniques that enable efficient training of our flagship models on our largest custom built supercomputers. The models we train are key ingredients to the AI research progress at OpenAI and the field as a whole, and we continually incorporate learnings from our entire research org into our training platform. About the Role As a Software Engineer, Networking you will design and implement custom networking collectives that are tightly integrated into our training stack. We’re looking for people who have a background in low level performance critical software. Experience with collective communication is a bonus. 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: Collaborate closely with ML researchers to design and implement efficient collective operations in C++ and CUDA. Ensure that our largest training jobs take full advantage of the different network transports used in our supercomputers. Work on simulations to inform our future supercomputer network designs. You might thrive in this role if you: Have written distributed algorithms using RDMA in the past. Are comfortable writing low level performance sensitive CPU and/or GPU code. Are familiar with network simulation techniques. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voic

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 builds the data, environments, graders, training methods, and feedback loops that shape what OpenAI’s next agents can do and what they are like to work with, then carries those improvements through major training runs and into products used by people every day. About the Role As a member of the Agent Post-training Personality team, you will help make OpenAI’s agents exceptional collaborators. You will study what makes an agent thoughtful, clear, perceptive, appropriately proactive, and genuinely easy to work with, then translate those insights into evals, training data, reward signals, and model improvements. We use “personality” to mean much more than writing style or general likability. It includes whether an agent understands what the user is trying to accomplish, communicates with good judgment, adapts to context, asks useful questions, handles disagreement honestly and takes initiative at the right moments. The goal is to create a strong, tasteful default that can adapt to different people and situations. This work combines behavioral research, product thinking, research and communication taste. You will collaborate with product teams, human experts, and researchers across post-training and pretraining to ensure that improvements survive the full trai

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, you will research and develop improvements to memory usage and personalization in OpenAI's frontier models. Our team works on reinforcement learning, dataset creation, evaluations, and other post-training methods. We partner closely with research and product teams across the company to realize the vision of a truly personalized ChatGPT. We're looking for individuals who have a background in frontier model post-training, are able to iterate quickly, and who are passionate about product-driven research. 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 memory use 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: Are passionate about personalization and building personalized assistants. Have experience working with user signals and human data to turn feedback into reliable signals for training and evaluation. Have a deep understanding of frontier model post-training and machine learning applications. Value principled approaches and research craftsmanship. Are comfortable diving into a lar

About the Team OpenAI’s Safety teams work to ensure our products are safe, trusted, and resilient as frontier AI systems scale globally. We tackle some of the company’s most important challenges across understanding and preventing misuse and misalignment, intercepting fraud and abuse, and protecting vulnerable users. We are hiring Data Scientists to help build the analytical foundations that allow OpenAI to deploy increasingly capable AI responsibly. We are hiring Data Scientists across several teams that contribute to safety in different ways, including: Safety Systems Integrity Product Policy This is a high-impact role operating at the intersection of product, safety, policy, and research. About the Role As a Data Scientist, Safety, you will help solve complex and ambiguous problems where rigorous analysis directly informs critical decisions. Depending on your background and team alignment, you may work on areas such as: Measure harmful or abusive behavior across OpenAI’s products Detect fraud, manipulation, coordinated misuse Evaluate and improve safety classifiers, rules systems, mitigation systems, and human review workflows Design experiments and causal analyses to understand product, policy, and mitigation impacts Build prevalence estimators, dashboards, monitoring systems, and executive decision frameworks Diagnose gaps in safety and integrity systems using behavioral and product data, and help quantify and navigate false positive / false negative tradeoffs Translate ambiguous safety risks into measurable problems and evidence-based recommendations Partner with Product, Engineering, Policy, Research, and Operations teams to improve safety outcomes Build zero-to-one analytical systems in rapidly evolving domains Ideal Candidate We’re looking for strong Data Scientists who thrive in ambiguous, high-leverage environments. You may be a fit if you have: Strong statistical reasoning and analytical judgment Experience with experimentation, causal inference, or obse

About the Team Business Systems / Enterprise Platform Technology builds the internal systems, data foundations, workflow infrastructure, and enterprise platforms that help OpenAI operate at scale. The EPT AI Pod builds AI-native internal apps, MCP connectors, multi-agent workflows, and reusable platform capabilities across Finance, People, and GTM. About the Role As an Enterprise Applied AI Engineer, you will build internal apps for enterprise operations and the shared platform components those apps run on. This includes MCP connectors, multi-agent orchestration, data architecture, evals, monitoring, auditability, and governance. We’re looking for a hands-on engineer who is strong in Python, system design, enterprise integrations, data architecture, and applied AI systems. You should be excited to turn ambiguous business workflows into reliable internal products and shared infrastructure. In this role, you will: • Build internal apps for enterprise operations across Finance, People, and GTM • Build MCP connectors and enterprise integrations with strong auth, permissions, idempotency, retries, and rate-limit handling • Design end-to-end multi-agent workflows with tool routing, human approvals, audit trails, and safe action boundaries • Design data architecture for operational AI systems, including ingestion, schemas, quality checks, lineage, and governance • Build evals, monitoring, metrics, and regression tests for agentic workflows • Create reusable infrastructure, patterns, and components that other enterprise teams can build on • Partner with system owners and business owners to turn messy enterprise workflows into reliable internal products You might thrive in this role if you: • Have strong Python engineering skills for backend services, MCP connectors, agent/tool workflows, eval harnesses, and data ingestion jobs • Have strong system design skills across shared infrastructure, app architecture, reliability, and scaling • Have experience building internal apps,

About the Team The Personal AGI team is responsible for training and improving pre-trained models to be deployed into ChatGPT, the API, and potential future products. The team partners closely with research and product teams across the company, and conducts research as a final step to prepare for real world deployment to millions of users, ensuring that our models are safe, efficient, and reliable. About the Role As a Research Engineer / Scientist, you will research and develop improvements to our models. Our team works in research areas combining reinforcement learning and products. We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models. An ideal candidate is passionate about product-driven research. 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 to improve model capability and performance. Collaborate closely with the other research and product teams, allowing customers to optimize their own models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. You might thrive in this role if you: Have a deep understanding of machine learning and machine learning applications. Have a working knowledge of relevant models, and building evaluations for model capability improvement. Are comfortable diving into a large ML codebase to debug. Thrive in a 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 systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and

About The Team The Data Understanding team is responsible for creating the high quality datasets and their quantized representation for OpenAI. This includes synthesizing data, building VQ representations, and processing, filtering, deduplication, quality control, and tokenization so it can be used effectively in big model training runs. About The Role We're looking to advance how OpenAI builds and understands pretraining data at scale. You'll treat data quality and curation as core research problems: developing new methods to select, combine, and transform data; creating datasets that improve model capabilities; and designing rigorous experiments to understand how data choices and interventions affect model learning and downstream behavior. You'll work closely with frontier models and web-scale data to build evidence for which approaches work and why, then translate successful research into scalable data processing pipelines We Expect You To Have a strong track record of new or improved ML ideas, through publications, projects, or applied research. Own and drive a research agenda, from choosing the right problems to carrying long-running work through to impact. Be excited by OpenAI’s empirical, collaborative approach to research. Nice To Have Thoughtfulness about AI’s impact, including privacy, provenance, and data quality. Experience building high-performance deep learning or large-scale data processing systems. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer

About the Team The RL and Reasoning team drives the core reasoning paradigm and has created groundbreaking innovations such as o1 and o3. They focus on pushing the boundaries of reinforcement learning research, building next-generation generative models, and deploying them at scale. About the Role As a Research Engineer/Research Scientist at OpenAI, you will advance the frontier of AI alignment and capabilities through cutting-edge RL methods. Your work will sit at the heart of training intelligent, aligned, and general-purpose agents, including the systems that power various models. We’re looking for people who have a background in reinforcement learning research, are able to iterate quickly, and are proficient at coding. 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. You might thrive in this role if: You love being on the cutting edge of RL and language model research. You’re a self-starter who takes initiative and ownership of ideas, driving them to completion. You value principled approaches, simple experiments in tightly-controlled settings, and reaching trustworthy conclusions which stand the test of time. You thrive in a fast-paced, dynamic, and technically complex environment where rapid iteration is key. You’re comfortable diving into a large ML codebase to debug and improve it. You have a deep understanding of machine learning and machine learning applications. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the ful

About The Team The Data Understanding team is responsible for creating the high quality datasets and their quantized representation for OpenAI. This includes synthesizing multimodal data, building VQ representations, and processing, filtering, deduplication, quality control, and tokenization so it can be used effectively in big model training runs. About The Role We’re looking to advance how OpenAI prepares, curates, synthesizes and understands multimodal data at scale. You’ll work on research and production problems like synthesizing multimodal content (images, audio, and video) and their supervisions, improving noisy data pipelines, building better quality filters, using models to automate data prep, and measuring whether changes in the dataset improve model performance. We Expect You To Have a strong track record of new or improved ML ideas, through publications, projects, or applied research. Own and drive a research agenda, from choosing the right multimodal data problems to carrying long-running work through to impact. Be excited by OpenAI’s empirical, collaborative approach to research. Nice To Have Experience with multimodal learning, audio, vision, video, synthetic data, or data-centric ML. Thoughtfulness about AI’s impact, including privacy, provenance, and data quality. Experience building high-performance deep learning or large-scale data processing systems. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of

About the Team The Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models and their deployment in the real world. Learn more about OpenAI’s approach to safety. Building on the many years of our practical alignment work and applied safety efforts, Safety Systems addresses emerging safety issues and develops new fundamental solutions to enable the safe deployment of our most advanced models and future AGI, to make AI that is beneficial and trustworthy. About the Role At OpenAI, we're dedicated to advancing artificial intelligence, and we know that creating a secure and reliable platform is vital to our mission. That's why we're seeking a software engineer to help us build out our trust and safety capabilities. In this role, you'll work with our entire engineering team to design and implement systems that detect and prevent abuse, promote user safety, and reduce risk across our platform. You'll be at the forefront of our efforts to ensure that the immense potential of AI is harnessed in a responsible and sustainable manner. Your Responsibilities: Architect, build, and maintain anti-abuse and content moderation infrastructure designed to protect us and end users from unwanted behavior. Work closely with our other engineers and researchers to utilize both industry standard and novel AI techniques to measure, monitor and improve AI models’ alignment to human values. . Diagnose and remediate active incidents on the platform and build new tooling and infrastructure that address the root causes of system failure. You might thrive in this role if: You have built and run production services in a high growth, rapidly scaling environment. You can debug live issues and restore systems quickly. You have worked on content safety, fraud, or abuse, or are motivated and excited to work on present-day (“now-term”) AI safety. You have experience with Python or with modern languages such as C++, Rust, or Go, and are able to quickly ramp up on Py

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 Our team analyzes inference stack performance across the application, model, and fleet layers to identify bottlenecks and drive faster, cheaper inference. We combine systems profiling, benchmarking, and analysis to understand where time and cost are spent, then turn that understanding into performance optimizations and models that project performance and capacity needs for future launches. About the Role In this role, you will model inference performance across application, model, and fleet layers with higher fidelity. You will build cost-to-serve estimates from microbenchmarks and create tools that help cross-functional teams reason about latency, capacity, utilization, and cost tradeoffs. In this role, you will Build and refine performance models that translate microbenchmark results into cost-to-serve estimates. Analyze inference workloads end to end across applications, models, and fleet infrastructure. Enhance tooling to identify bottlenecks across layers for latency and throughput. Partner with other teams to turn performance insights into concrete improvements and project how future changes affect inference. You might thrive in this role if you: Enjoy reasoning from first principles about distributed systems, model inference, and hardware efficiency. Are comfortable working across abstraction layers, from application behavior to kernels, accelerators, networking, and fleet scheduling. Have deep expertise with performance profiling, benchmarking, analysis, and optimization. Enjoy collaborating with engineering and research teams to improve real production systems. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve o

About the Team Models are becoming increasingly capable—moving from tools that assist humans to agents that can plan, execute, and adapt in the real world. Mitigating the frontier risks resulting from these capabilities is paramount to OpenAI’s ability to continue deploying models safely. The Preparedness team is dedicated to addressing these critical risks. Our work includes: Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. Mitigation. Keeping misuse and misalignment safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework , and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. About the Role We are seeking exceptional researchers who can push the frontier of safety mitigations. You will help derisk frontier models by developing novel safety mitigations, developing and applying new techniques from domains like interpretability, control, and alignment to ensure the safety of OpenAI’s deployed models. You will play a critical role in defining how a safe AI system should look in the future at OpenAI, making a significant impact on our mission to build and deploy safe AGI. This role requires strong technical depth and close cross-functional collaboration to ensure our safety mitigations are enforceable, scalable, and effective. We seek researchers who can partner with experts across domains such as misalignment, cybersecurity, and biology in order to develop the best possible end-to-end safety stack. In this role, you will: Work on identifying emerging AI safety risks and new methodologies for exploring and mitigating the impact of such risks Build (and then continuously refine) the evaluations that enable us to assess the extent of these risks; this might include worki

About the team Models are becoming increasingly capable—moving from tools that assist humans to agents that can plan, execute, and adapt in the real world. Mitigating the frontier risks resulting from these capabilities is paramount to OpenAI’s ability to continue deploying models safely. The Preparedness team is dedicated to addressing these critical risks. Our work includes: Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. Mitigation. Keeping misalignment safeguards, alignment tools, and on track to adequately address extreme threats that might arise in the future. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework , and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. About the role Preparedness is hiring strong technical executors to support preparations for accelerated AI development, which may culminate in recursive self-improvement. This work relies on anticipating misalignment risks that might exist in the future, but might not exist now; so it’s especially important that people in this role are tasteful and strategic. The role is wide-ranging, covering any mitigation for loss of control risk, spanning the design and implementation of better pre-deployment risk-assessment , control measures , RSI-relevant training interventions, and turning one’s technical work into established institutional practices and external-facing communications. Below is a subset of our focus areas: Scalable oversight: Establishing practices for model misbehavior monitoring and oversight which remain effective in superhuman model capability regimes, with a focus on bridging from today’s monitoring approaches to future-proof ones. Automated auditing: As model capabilities increase, we’ll increasingly rely on automated approaches for finding the most severe forms of model misalignments. We’ll both need to s

Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? The role will lead a team of Account Executives primarily responsible for new business revenue in the North America Region. This person will be responsible for segment strategy and planning, building, and running a high performing team. Goals are focused on accelerating logo and revenue growth with a concentration on Fin. We are looking for a highly effective leader who excels at attracting and developing talent, inspiring others, and working cross-functionally to build efficient and customer-centric sales processes. This leader will also play a critical role in developing and executing our value-led sales strategy. For this big challenge, we are looking for an innovative, agile, and resilient Sales Leader to help us write the next chapter in the AI-first customer support space. What will