Safety Response Operations Lead in United States

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As a Senior QA Engineer, you will be the first dedicated QA hire for the Safety Engineering Group, which is responsible for building the infrastructure and policies that make Roblox the safest online community in the world. You will report to the QA Engineering Manager for Universal Apps and collaborate across the Safety organization to own end-to-end test strategies for high-stakes, 24/7 incident response systems and parent-facing safety features. This role is a unique opportunity to shape the quality culture of a company-level mandate from the ground up. You will: Partner with Engineering and Product to define and maintain comprehensive, risk-based test coverage for Safety features and systems. Own the end-to-end test strategy for Safety initiatives, including functional, regression, integration, and edge-case validation. Leverage and expand internal automation frameworks to automate critical user flows and drive API-first validation strategies. Identify high-impact automation opportunities and incorporate industry best practices to design robust, abuse-resistant test scenarios. Develop, track, and report on quality metrics (e.g., defect trends, coverage gaps) to proactively surface relea

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About The Role Millions of people rely on Notion to do their most important work, and protecting that trust is foundational to everything we build. We’re looking for a hands-on Detection Engineer to build and operate the systems and workflows we use to detect and respond to attacks across Notion’s cloud-native environment. You’ll ship high-signal detections, improve the platform that powers them, participate in incident response, and help shape how detection and response engineering scales at Notion. You’ll work closely with Engineering, Corporate Security, and Infrastructure, with broad latitude to identify gaps, prioritize investments, and build what’s needed next. We view detection and response as a software engineering discipline: detections are code, platforms are products, and measurement matters What You'll Achieve Design and maintain high-signal detections across cloud, identity, endpoints, and SaaS environments. Build and improve the detection platform, including rule lifecycle management, tuning, measurement, and rollout safety. Develop tooling and automation that accelerate triage, enrichment, investigation, and detection

About the Team OpenAI’s Platform team powers how millions of developers and enterprises build with our models. We provide APIs and agentic solutions used by global startups and fortune 500s. We work closely with product, engineering, design, and go-to-market to build a world-class platform that pushes the frontier of AI capabilities. About the Role As a Data Scientist on the Platform team, you will drive a data-driven culture for OpenAI’s API and B2B solutions. You’ll define the metrics that matter for developer success and enterprise value, measure the impact of new models and features, and partner with PMs and engineers to improve model quality, reliability, latency, and cost. Your work will shape how thousands of products adopt agentic AI. 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 Embed with the Platform product team as a trusted partner, uncovering ways to improve developer experience, reliability, and usage growth Define north-star metrics across the developer funnel (activation, retention, growth), as well as latency/cost guardrails for new features and models Design and interpret A/B tests and controlled rollouts (e.g., new model versions, pricing/limits, new API features, new B2B products) Build source-of-truth dashboards and self-serve data tools for product, engineering, and go-to-market teams Translate product learnings into actionable feedback for Research (e.g., failure modes, eval gaps, model response quality) You might thrive in this role if you have 5+ years in a quantitative role in ambiguous, high-growth environments (platforms, APIs, or B2B products a plus) Depth in SQL and Python, with a track record proposing, designing, and running rigorous experiments Experience defining and operationalizing metrics from scratch (including reliability/latency/cost and safety) Strong cross-functional communication with PMs, enginee

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 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 We’re hiring Software Engineers to join our broader Infrastructure organization, which supports multiple high-impact teams. Depending on your interests and experience, you could work on one of several focus areas—including Core Distributed Systems, Reliability Engineering, Observability, Developer Productivity or Cloud Infrastructure. About the Role All teams are deeply collaborative, work on mission-critical services, and are responsible for building distributed, scalable infrastructure to bring OpenAI’s technology to the world through products like ChatGPT and the OpenAI API. You’ll work closely with stakeholders to understand infrastructure, data and compute needs, setting the technical strategy that supports cutting-edge research and product development. This is a critical role for someone who is passionate about solving complex engineering problems at scale, ensuring their performance, scalability and reliability Team Focus Areas Distributed Systems: Owning and building important, highly scalable, available, performant, and reliable distributed systems (and their building blocks) to power the entire stack at OpenAI Systems Engineering: Work across layers of the stack—debugging system bottlenecks, evolving core infrastructure, and solving novel problems in performance and scalability. Reliability Engineering: Build scalable, fault-tolerant systems and lead efforts around service health, incident response, and resilience. Observability: Design and maintain observability tooling (metrics, logs, tracing) to give teams visibility into production systems at scale. Developer Productivity: Create tools, environments, and workflows that help engineers ship high-quality software faster and more safely. Cloud Infrastructure: Own the cloud-native infrastructure (compute, networking, storage) that underpins all services and research workloads. Databases: Building high performance, distributed database systems that power all of OpenAI's product stack. In this

About the Team The Agent Safety team works to ensure that increasingly capable AI agents act safely, exercise sound judgment, and remain aligned with user intent. Our mission is to reduce the probability of severe unintended outcomes from increasingly capable AI agents while preserving their ability to act effectively and autonomously. Our work spans three areas: Training: Create training methods, environments and data that teach agents to make better decisions in consequential situations. We turn real-world failures into training signals that prevent similar incidents, and identify precursor behaviors and mitigations to address emerging risks. Measurements: Build evaluations and production metrics that identify emerging risks and measure whether our interventions work. Oversight: Develop oversight and system mitigation mechanisms that reduce harmful actions while preserving useful autonomy (for example future versions of auto-review ). About the Role We’re looking for strong executors with excellent judgment, comfort with ambiguity, and an understanding of frontier model research. You don’t need prior safety or alignment experience, we also welcome people that recently realized that alignment and safety is a critical area to contribute to. 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: Train and evaluate frontier models to reduce harmful or misaligned agent actions, forming clear hypotheses and executing independently through ambiguity. Mine incidents and build scalable measurement, data-processing, and evaluation systems that turn real failures into repeatable safety signals. Collaborate closely with post-training, capabilities, oversight, and pre-training partners to ship research-backed mitigations into large-scale training and agent systems. You might thrive in this role if you: Have demonstrated strength in research engineering, ML en

About the Team The Agent Safety team works to ensure that increasingly capable AI agents act safely, exercise sound judgment, and remain aligned with user intent. Our mission is to reduce the probability of severe unintended outcomes from increasingly capable AI agents while preserving their ability to act effectively and autonomously. Our work spans three areas: Training: Create training methods, environments and data that teach agents to make better decisions in consequential situations. We turn real-world failures into training signals that prevent similar incidents, and identify precursor behaviors and mitigations to address emerging risks. Measurements: Build evaluations and production metrics that identify emerging risks and measure whether our interventions work. Oversight : Develop oversight and system mitigation mechanisms that reduce harmful actions while preserving useful agent autonomy (for example future versions of auto-review ). About the Role This role focuses on oversight and system-level mitigations that enable increasingly capable agents to operate safely and autonomously in real environments. We prioritize building oversight systems that are used in practice today, both internally and externally (see our recent work on action monitoring for codex and former code review ). We also study longer-term questions about how increasingly capable agentis systems can be supervised, constrained, and corrected. We’re looking for a safety&security minded researcher or engineer who can reason rigorously about security boundaries and agent behavior, then build and test practical mitigations. A background in AI control or security is welcome but not required. 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: Design, build, and evaluate system-level controls for agent actions like agent-based review. Plan how they fit in a broader syste

About the Team The Safety Systems org is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society and is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Safety Engineering team builds the platforms and tools that make OpenAI’s models safe to use in the real world. We partner closely with researchers, product teams, and policy to turn safety ideas into reliable, scalable systems: measuring risk, enforcing safeguards, and continuously improving how models behave in production. Our work sits at the intersection of product engineering, data, and AI, and directly shapes how millions of people experience OpenAI’s technology. About the Role We’re looking for a self-starter engineer who loves building products in an iterative, fast-moving environment—especially internal tools that unlock real-world impact. In this role, you’ll build full-stack tooling for our Safety Systems teams that directly improves the safety and reliability of OpenAI’s models, including in sensitive areas like mental health and other vulnerable-user protections. Your work will increase the team’s velocity in identifying and fixing safety issues and help tighten the feedback loop between policy, data, and the model training cycle. In this role, you will: Own the end-to-end development of internal tools that help improve the safety of OpenAI’s models (with a focus on areas like mental health and other vulnerable-user protections) Partner closely with Safety Systems researchers, engineers, and model policy creators to understand workflows, pain points, and requirements—and translate them into durable product solutions Build full-stack experiences to support core model policy workflows, such as labeling and inspecting data, analyzing and reviewing failure cases, and surfacing insights for iteration Optimize internal applications f

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As a Senior Child Safety Intelligence Analyst on Roblox’s Safety Intelligence Team, you will be on the front lines protecting the platform’s youngest and most vulnerable users. This is a proactive intelligence role focused on identifying, tracking, and disrupting systemic threats to minors, to include child sexual exploitation and abuse (CSAE), grooming behaviors, peer-to-peer harassment, financial minor extortion (sextortion) and bad-actor networks trying to exploit platform features to victimize minors. You will blend quantitative and qualitative data, open-source intelligence (OSINT), behavioral analysis, and deep knowledge of online culture to uncover adversarial trends before they impact the platform ecosystem, and provide your analysis to teams across Roblox and company leadership. Your insights will directly shape automated detection logic, product safety features, and platform policy. Psychological Wellness Note: This role involves exposure to highly sensitive and potentially disturbing themes regarding the exploitation of minors. Roblox offers resources to support employees handling this challenging work. This role is based in San Mateo, CA and requires employees

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

About the Team OpenAI is at the center of some of the highest-impact multimodal work in AI. ChatGPT serves a massive global audience, and enables diverse interactions via text, speech, and visuals. As interactive surfaces grow, models also need to adapt to emerging harm, understand user intent and situational context, and respond appropriately. The Chat and Multimodal Safety team is responsible for ensuring that OpenAI’s increasingly multimodal models and products behave safely across these experiences. We develop the research, training methods, and evaluations needed to make these experiences safe. Our work sits at the frontier of responsibly deploying powerful AI, in close partnership with Personal AGI, io, model training, and product teams. About the Role As a Researcher on the Chat and Multimodal Safety team, you will help shape how frontier models perceive and reason the world, and translate that understanding into safe behavior. We’re looking for people who combine deep technical expertise with strong safety judgment. Strong candidates often bridge perception and language: they may have built vision-language models, worked on modality fusion or image encoders, developed multimodal post-training or evaluations, or advanced safety for image, video, or audio systems. 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: Define and advance multimodal safety research for text, vision, and audio, connecting perception and semantic understanding to safe model behavior. Build training and evaluation methods for VLMs, including post-training, safety evals, and interventions that help models respond safely and appropriately in varied contexts. Collaborate closely with Personal AGI, Consumer Devices, and product/model teams to translate research into safer ambient, embedded, and personalized multimodal experiences. You might thrive in this role if you:

About the Team The Safety Systems team is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society and is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Model Safety Research team aims to fundamentally advance our capabilities for precisely implementing robust, safe behavior in AI models, and to leverage these advances to make OpenAI’s deployed models safe and beneficial. This requires a breadth of new ML research to address the growing set of safety challenges as AI becomes more powerful and used in more settings. Key focus areas include how to enforce nuanced safety policies without trading off helpfulness and capabilities, how to make the model robust to adversaries, how to address privacy and security risks, and how to make the model trustworthy in safety-critical domains. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. About the Role OpenAI is seeking a senior researcher with passion for AI safety and experience in safety research. Your role will set directions for research to enable and empower safe AGI and work on research projects to make our AI systems safer, more aligned and more robust to adversarial or malicious use cases. You will play a critical role in shaping how a safe AI system should look like in the future at OpenAI, making a significant impact on our mission to build and deploy safe AGI. In this role, you will: Conduct state-of-the-art research on AI safety topics such as RLHF, adversarial training, robustness, and more. Implement new methods in OpenAI’s core model training and launch safety improvements in OpenAI’s products. Set the research directions and strategies to make our AI systems safer, more aligned and more robust. Coordinate and collaborate with cross-functional team

About the Team Safety Systems works to ensure OpenAI’s most capable models can be developed and deployed responsibly. Our work spans evaluations, safeguards, red teaming, deployment decisions, and the systems that help OpenAI understand and reduce risk as models become more capable and widely used. Within Safety Systems, the Trustworthy AI team is growing its safety transparency function: a practice focused on helping external audiences understand OpenAI’s technical safety work with greater clarity, rigor, and continuity. We create and improve the public artifacts that explain how our systems are evaluated for safety, what safeguards we build, what decisions we make, and where uncertainty remains. This work includes system cards, the Deployment Safety Hub, safety-related blogs, public governance documents, and other outputs that communicate technical safety topics to external audiences. It also includes building new ways to make technical safety information easier to understand, navigate, and use—including AI-assisted workflows, data visualizations, and interactive tools that make complex technical work more legible over time. About the Role We are looking for a Safety Transparency Editor to own the editorial quality of key safety transparency artifacts and systems. This is a hands-on role for someone who can write crystal-clear, pitch-perfect explanations of the hardest and highest-stakes technical safety topics that OpenAI tackles, and who can lean into AI to build systems that help the broader organization do this work better. Your core responsibility is to shape and execute how our technical safety work is externally communicated: identifying the narrative thread, exercising judgment about which details matter, determining where additional context, explanation, or supporting evidence is needed, translating complexity without sacrificing precision, and helping external audiences understand both the safety measures we’ve taken and the uncertainties that remain. To

About the Team The Safety Systems team is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society, and is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Safety Oversight Research team aims to fundamentally advance our capabilities to maintain oversight over frontier AI models, and leverage these advances to ensure OpenAI’s deployed models are safe and beneficial. This requires a breadth of new ML research in the areas of human-AI collaboration, reasoning, robustness, and scalable oversight to keep pace with model capabilities. We invest heavily in developing novel model and system-level methods of identifying and mitigating AI misuse and misalignment. Our goal is to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. About the Role OpenAI is seeking a senior researcher with a passion for AI safety and experience in safety research. Your role will set directions for research to maintain effective oversight of safe AGI and work on research projects to identify and mitigate misuse and misalignment in our AI systems. 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. In this role, you will: Develop and refine AI monitor models to detect and mitigate known and emerging patterns of misuse and misalignment. Set research directions and strategies to make our AI systems safer, more aligned, and more robust. Evaluate and design effective red-teaming pipelines to examine the end-to-end robustness of our safety systems, and identify areas for future improvement. Conduct research to improve models’ ability to reason about questions of human values, and apply these improved models to practical safety challen