User Growth Senior Manager in San Francisco

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's LLM inference platform delivers frontier performance for open-source models with best-in-class elasticity and developer experience, made in part possible by our custom runtime with GPU memory snapshots and multi-cloud substrate . We're looking for a leader to own the direction and execution of this platform to continue to establish us as the clear market leader, working closely with customers like Cognition, Doordash, Ramp, and many more. You'll be leading a group of highly talented engineers working on our market-leading LLM inference offering, spanning the serving stack, routing infrastructure, internal agentic optimization platform, and the user-facing product surface area. This is a hands-on leadership role — expect to split your time between technical contribution, product shaping and people management depending on what the team needs. You'll set direct

About the Team : We build core first-party app experiences in ChatGPT and Codex, define the primitives for high-quality app third-party app experiences, and collaborate with best-in-class partners across consumer and enterprise categories to bring delightful experiences to our customers. About the Role: We are hiring a Product Manager to shape and scale the app ecosystem across ChatGPT and Codex. This person will own both 1P product experiences and partner-led launches, translating user needs, model capabilities, platform constraints, developer and partner requirements, and enterprise controls into products that feel delightful, reliable, and safe. This position is based in San Francisco, CA, with relocation assistance available. In this role, you will: Develop the strategy and roadmap for ChatGPT and Codex app ecosystem experiences across consumer and enterprise use cases. Build and ship high-quality first-party app experiences that demonstrate the best of what apps can do inside ChatGPT and Codex. Collaborate with best-in-class partners to create app experiences that solve real user and business workflows. Define the product foundations and quality standards needed for a trusted app ecosystem. Lead cross-functional execution across engineering, design, research, partnerships, GTM, legal, privacy, security, support, and data/evals. Use customer, user, partner, and model-behavior insights to prioritize the roadmap and improve post-launch performance. You might thrive in this role if you: Have built and scaled consumer or enterprise product experiences with strong product taste and measurable user impact. Have built app platforms, marketplaces, partner ecosystems. Are technically fluent enough to reason about MCPs, APIs, SDKs, and model/product constraints. Can move fluidly between strategy, product, partner judgment, and operational execution. Communicate crisply in writing and bring clarity to ambiguous, fast-moving product areas. Care deeply about user trust, safe

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE We’re looking for a seasoned Frontend Engineer to craft performant and delightful user experiences across Baseten’s core platform. You’ll own critical parts of our web application stack and collaborate cross-functionally with product, design, and backend teams to launch impactful features that help users deploy and manage AI systems at scale. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Core Product team: Rolling Deployments Model APIs for frontier models Model training built for production inference RESPONSIBILITIES Design, implement, and maintain responsive, accessible, and user-friendly frontend interfaces using React and TypeScript Collaborate closely with product designers to turn complex ideas into elegant, intuitive UIs Optimize application performance and reliability, with a focus on rendering speed and responsiveness Drive major frontend initiatives, including partnering with backend teams to define APIs and test and refine end-to-end flows Establish best practices, and mentor other engineers on frontend technologies Build reusable component libraries and frontend infrastructure that accelerate product development Partner with backend and platform teams to define and refine APIs and end-to-end flows REQUIREMENTS 5+ years of experience building production-grade web applications Deep expertise in React, TypeScript, and modern web development tooling Track record of bu

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Plaid’s mission is to unlock financial freedom for everyone by making money movement and access to financial data simple and secure. As a Fullstack Software Engineer, you will design and build the systems and experiences that power how millions of people connect to their finances. You will work across the stack, building scalable backend services and APIs while also crafting intuitive, high-quality frontend experiences that bring those systems to life. This role is ideal for engineers who enjoy switching between backend problem-solving and frontend user experience work, and who are excited to grow their impact across both. You will collaborate closely with product managers, designers, and other engineers to ship products that are reliable, secure, and delightful to use. At Plaid, engineers take ownership early, contribute to architectural decisions, and see their work reach millions of users. Responsibilities: Build across the stack. Design, develop, and maintain scalable backend services and APIs, as well as intuitive, high-quality frontend applications that bring those systems to life. Collaborate cross-functionally. Partner closely with product managers and designers to define requirements and de

What you’ll do Partner with medical image reconstruction scientists / engineers to build ML components that improve reconstruction quality, speed, robustness, or quantitative accuracy. Define training/evaluation pipelines, datasets, and metrics that map to user needs and design requirements. Productionize models: inference performance, reproducibility, monitoring for drift/regressions, and safe fallbacks. Collaborate on hybrid algorithms, incorporating physics and learned priors, denoisers, learned regularizers, and quality estimation. Help build tooling for rapid experimentation as well as rigorous verification of algorithm changes. What we’re looking for Strong applied ML experience plus comfort with signal processing / imaging or adjacent domains. Ability to move fluidly between research prototypes and production-quality systems. Strong evaluation discipline: metrics, ablations, data leakage avoidance, and reproducibility. A demonstrated track record of applying ML to physics-based or inverse problems (i.e., shipped projects, a portfolio, or publications.) Useful experience ML for imaging/inverse problems (or adjacent) with strong evaluation discipline and comfort with GPU performance constraints. Pragmatic production mindset: reproducible training/inference, regression testing, and safe deployment in high-stakes contexts. A background in computational physics or scientific computing. Leverage ML-based methods such as PiNNs and Neural Operators to solve partial differential equations arising in ultrasound simulation and imaging. Experience in Agentic-SciML is a plus. Hands-on experience with data curation for ML: building datasets from messy, real-world sources, defining ground truth, and managing labeling or simulation pipelines. Background in data assimilation: combining observations with physics-based models (Kalman filtering, variational methods, ensemble approaches, or learned variants).

At Datadog we’re growing our investment in AI and Developer focused events. As we scale this program we’re looking to hire a Program Manager on our Community team to support our content and advocacy team efforts across these events. The Datadog Technical Advocacy team are focused on our local user communities, and bringing our technical content directly to our customers globally. You’ll be responsible for planning and execution to deliver AI and Developer events, working across multiple teams at Datadog to ensure our event is high quality and a positive experience for our customers. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Growing Datadog’s presence at AI events and identifying opportunities for meetups, hands-on learning, and sponsored events, with a focus on AI or Developer events Planning technical programming for AI or developer events that Datadog hosts or sponsors Supporting AI and developer focused content at larger global events such as DASH, Datadog’s annual conference Tracking deadlines and deliverables for our content and events, including digital and physical assets, and working with vendors and procurement teams as needed to ensure event success Identifying and resolving risks and blockers for our event programing Maintaining our internal tools and public website for event agenda and speaker content Owning our onsite speaker experience for both internal and customer speakers Managing event programming onsite, coordinating rehearsals, staffing, and ensuring smooth onsite operations Collaborate closely with our Community teams, external stakeholders, and the VP of Community Create and refine processes; maintain focus on continual improvements, automat

About the Team OpenAI’s Network Engineering team within IT and Security advances the mission of deploying artificial general intelligence (AGI) for the benefit of all by delivering secure, scalable, and resilient network services. We build and operate the connectivity that supports OpenAI’s offices, labs, campuses, cloud environments, people, and devices. By combining strong network fundamentals with security, reliability, automation, and user-centered design, we enable impactful AI research, corporate operations, and product innovation. About the Role As a Network Engineer at OpenAI, you will design, operate, and continuously improve the global networks that connect our offices, labs, campuses, PoPs, cloud environments, people, and devices. The role spans strategic platform engineering and responsive production operations: you will shape architecture, standards, roadmaps, lifecycle plans, and automation while supporting incidents, escalations, and time-sensitive delivery. Operational signals will inform what we stabilize, simplify, standardize, or automate next. We work backward from user needs, investigate root causes, own outcomes end-to-end, and move quickly without compromising security. We are looking for a versatile engineer who can make pragmatic reliability and security tradeoffs, communicate clearly, and turn recurring operational work into durable platforms, tooling, and standards. You will partner across IT, Security, AppEng, Research, Applied, workplace teams, carriers, and vendors. In this role, you will: Design, implement, and operate secure, scalable enterprise networks across offices, labs, campuses, PoPs, cloud connectivity, and hybrid environments. Set strategic direction for network services through architecture, standards, roadmaps, lifecycle planning, capacity strategy, and measurable reliability outcomes. Own production operations, including on-call, incident response, escalations, and time-sensitive delivery, while protecting user experience,

About the Team The Communications team supports OpenAI’s mission by helping the organization communicate clearly, responsibly, and effectively with external audiences. We work closely with partners across the company to navigate complex topics, manage evolving narratives, and ensure OpenAI’s communications reflect our values and long-term goals. About the Role We’re looking for an exceptional PR professional to join our nimble, high-impact team to help share our progress toward developing Artificial General Intelligence (AGI) that benefits everyone. This person will partner with the Consumer Lifestyle Communications Lead to develop sustained campaigns that shape how people understand and experience our consumer products. Working across marketing, product, community, and global communications, they will craft compelling stories and integrated campaigns that showcase our products’ creativity, usefulness, and positive impact. They will lead proactive user and seasonal storytelling that makes AI feel more relatable, trusted, and useful in everyday life. This role reports to the Consumer Lifestyle Communications Lead. 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: Lead proactive user and seasonal storytelling that makes technology matter to everyday people. Support communications campaigns that showcase ChatGPT’s distinctive benefits and capabilities for global consumer audiences. Translate technical topics into clear, compelling narratives grounded in real-world impact. Build trusted relationships with consumer and lifestyle media, and manage inbound press inquiries across a range of topics. Partner with marketing, product, community, and global communications teams to deliver integrated campaigns. Spot emerging cultural and consumer trends, and move quickly to turn the right moments into relevant, high-impact storytelling opportunities. Identif

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 Legal team is building the next generation of AI-powered products and experiences for the legal industry. We are exploring how advanced AI systems can transform legal workflows, improve access to information, and enable legal professionals and organizations to work more effectively. As a founding member of the Legal engineering team, you will help define the technical foundation for this new product area from the earliest stages. You’ll operate at the intersection of AI, product, and real-world legal workflows—identifying opportunities, building prototypes, and turning emerging ideas into scalable products that can create meaningful impact. We operate with a startup-like mindset inside OpenAI: small teams, rapid iteration cycles, and a willingness to explore bold ideas, learn quickly, and adapt based on user feedback. Our goal is to build products that meaningfully improve how legal professionals work while leveraging OpenAI’s cutting-edge models and infrastructure. About the Role As a Founding Full-Stack Software Engineer on the Legal team, you will help imagine, build, and scale new AI-powered products for the legal industry. You’ll work across the stack to design intuitive user experiences, build robust backend systems, and create the foundations for products used by legal professionals and organizations around the world. You’ll have significant ownership from the earliest stages—working closely with product, design, research, and go-to-market partners to understand customer needs, shape product direction, and deliver high-impact solutions. This includes rapidly prototyping new concepts, building production-quality applications on top of OpenAI’s platforms, and developing new technical approaches when existing systems are not sufficient. We’re looking for engineers who thrive in ambiguity, have strong product instincts, and enjoy building from 0→1. You should be comfortable moving quickly, making thoughtful technical decisions, and taking owner

About the Team The Core Models team helps shape how OpenAI’s frontier models are built, measured, and launched. We work across Research, Engineering, Model Design, Data Science, and Product to turn advances in model capabilities into reliable, useful experiences for people. Our scope includes model planning and launches as well as building data flywheels, evaluations and measurement systems to ensure our models have strong capabilities and behavior. About the Role As a Product Manager for the Core Models team, you'll be at the forefront of defining and guiding the future of how our AI models work in real-world applications. You will connect user needs to model and systems decisions: how prompts are understood; how information is aggregated and made useful for training and evaluation data; and how capabilities move from research prototypes into the mainline model and launch stack. You will operate comfortably across research, infrastructure, and consumer product surfaces, creating clarity where ownership and technical boundaries are still emerging. 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: Translate user and product goals into clear model requirements, system architecture choices, and research priorities across query understanding, indexing, retrieval, ranking, tool boundaries, data, training, inference, and evaluation. Build closed learning loops that turn product usage, explicit feedback, and other user signals into datasets, evaluations, experiments, training priorities, and launch decisions. Define success across offline evaluations and online product metrics, balancing model quality, usefulness, latency, safety, reliability, and cost. Partner closely with post-training research, applied product engineering, Model Design, and Data Science to integrate capabilities into the mainline model stack. Create reusable platforms and operatin

About the Team The Monetization team is a cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products, including next-generation ads experiences that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to build measurement systems that connect ad interactions to meaningful advertiser outcomes while protecting user privacy. In this foundational role, you’ll design infrastructure for conversion signals, attribution, reporting, and feedback loops across OpenAI’s ads products. This role is ideal for engineers who have built large-scale ads measurement, data, experimentation, marketplace, or distributed systems and want to apply that experience in a highly ambiguous 0→1 environment. You’ll work across event collection and normalization, deduplication and matching, attribution and modeled measurement, privacy-safe aggregation, reporting, and high-quality labels for ads optimization. We are hiring engineers who can independently own complex systems, make sound technical tradeoffs, and help define what should be built. You’ll work closely with Ads Delivery, Ads ML, Product, Research, Privacy, Data Sc

About the Team The Personality & Model Behavior team, within OpenAI’s broader Personal AGI team conducts research on how to shape personalities and guide the behavior of models. We think about topics such as emotional intelligence, reasoning, and how models interact thoughtfully with users. We’re particularly interested in understanding how individual users want ChatGPT to behave, and creating personalized models that feel uniquely tailored to each user. We integrate this research into ChatGPT and other OpenAI products that are used by hundreds of millions of users. About the Role We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models, and in areas like reinforcement learning and reward modeling. An ideal candidate is passionate about product-driven research. In this role, you will: Conduct research around personalization, personality, and model behavior by leveraging and developing tools such as synthetic data, reward modeling, and reinforcement learning. Build robust evaluations and model training pipelines to facilitate our research. Innovate new post-training methods. 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: Have a deep understanding of machine learning and its applications. Have prior knowledge in training and optimizing models and building evaluations. Are willing to dive into large ML codebases to debug issues. Thrive in dynamic and technically complex environments. Have a track record of delivering innovative, out-of-the-box solutions to address real-world constraints. 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 o

About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers where they are and moves with them up the scaling curve. Our work focuses on three pillars: high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; performant, high-uptime, fault-tolerant training frameworks (training loop, state management, resilient checkpointing, deterministic orchestration, and observability); and distributed process management for long-lived, job-specific and user-provided processes. We integrate proven large-scale capabilities into a composable, developer-facing runtime so teams can iterate quickly and run reliably at any scale, partnering closely with model-stack, research, and platform teams. Success for us is measured by raising both training throughput (how fast models train) and researcher throughput (how fast ideas become experiments and products). About the Role As a Training: ML Framework Engineer, you will work on improving the training throughput for our internal training framework, while enabling researchers to experiment with new ideas. This requires good engineering (for example designing, implementing, and optimizing state-of-the-art AI models), writing bug-free machine learning code (surprisingly difficult!), and acquiring deep knowledge of the performance of supercomputers. In all the projects this role pursues, the ultimate goal is to push the field forward. We’re looking for people who love optimizing performance, understanding distributed systems, and who cannot stand having bugs in their code. Since our training framework is used for large runs with massive numbers of GPUs, performance improvements here will have a large impact. This role is based in San Francisco, CA. We use a

About the Team: The Shopping team is building the future of how people discover, evaluate, and purchase products through AI. Our mission is to help users make better purchasing decisions by combining OpenAI’s models with rich product information, merchant ecosystems, and personalized experiences. We sit at the intersection of AI, commerce, search, recommendations, and consumer product experiences, partnering closely with product, engineering, research, design, and business teams to reimagine shopping for the AI era. About the Role: As a Product Manager on the Shopping team, you’ll define and build the next generation of AI-powered shopping experiences within ChatGPT. You’ll be responsible for understanding user needs, identifying opportunities to improve product discovery and decision-making, and delivering experiences that help users confidently find and purchase the products that are right for them. You’ll work across a broad set of domains, including search, recommendations, personalization, merchant and product ecosystems, and conversational commerce. This role requires strong product judgment, comfort operating in ambiguity, and the ability to balance user value, business objectives, and technical constraints. You’ll partner closely with engineers, designers, researchers, and cross-functional stakeholders to bring new shopping experiences from concept to scale. This is an opportunity to help define an entirely new category at the intersection of AI and commerce, shaping how millions of users discover and buy products in the future. This position is based in San Francisco, CA, with relocation assistance available. In this role, you will: Define and drive the product vision for shopping experiences in ChatGPT. Partner with research teams to explore how AI can help users discover, evaluate, and confidently purchase products. Collaborate with cross-functional teams—including design, engineering, product, and go-to-market—to build and scale AI-native shopping experi