Memory Design Engineer Jobs

About the Team The Statsig team within OpenAI owns the experimentation, rollout, dynamic configuration, and analytics infrastructure that sits on the launch path for OpenAI products. Our systems help teams ship safely, evaluate product and model changes in production, and make high-confidence decisions from real-world usage. Statsig began as an independent company built around experimentation, feature management, and product analytics at scale. After Statsig joined OpenAI, the team began the next chapter: bringing that platform expertise and infrastructure into OpenAI as the experimentation and rollout foundation for every product we ship. This is infrastructure with a very direct product consequence. Teams working on ChatGPT, Codex, model measurement, consumer experiences including ads, business subscriptions, developer products, and shared platform systems depend on Statsig to evaluate configurations, move traffic safely, ingest experiment data, serve analytics, and roll changes forward or back when production reality demands it. We are at a critical point in the platform journey. Adoption is accelerating quickly across OpenAI, and the systems that were already important are becoming load-bearing for how the company launches. The infrastructure needs to stay fast under sharply increasing evaluation volume, reliable when more services depend on it, observable enough to debug quickly, and efficient enough to support OpenAI-wide scale. Recent SDK and server-side infrastructure work has already produced measurable wins in latency, reliability, memory usage, and compute efficiency across important services. The next phase is to make those gains systematic: a platform that can absorb rapidly growing product velocity while preserving low latency, data quality, operational safety, and developer trust. Based out of OpenAI's Bellevue office, we are a close-knit team that values in-person collaboration, technical depth, operational ownership, and building infrastructure that

About the Team The Statsig team within OpenAI builds the experimentation, feature rollout, dynamic configuration, and analytics systems that help OpenAI ship products with speed, safety, and evidence. Our work sits on the critical path for how product, engineering, research, and go-to-market teams learn from real-world usage and make high-confidence decisions. Statsig began as an independent company focused on helping builders move faster through trustworthy experimentation and feature management. After Statsig joined OpenAI, the team began the next chapter: bringing that deep product expertise, customer intuition, and mature platform infrastructure into OpenAI as the experimentation and rollout platform for every product we ship. Today, we support teams across ChatGPT, Codex, model measurement, consumer experiences including ads, business subscriptions, developer products, and the shared infrastructure that connects them. These teams rely on Statsig to safely introduce new capabilities, compare product and model behavior, measure impact, and roll changes forward or back with confidence. We are at a defining moment in the platform journey. OpenAI has the data, product surface area, and pace of innovation to learn faster than almost any organization in the world, but that potential only becomes real if teams can experiment responsibly, measure clearly, and roll out changes safely. Adoption of the platform is accelerating rapidly across the company, and recent SDK and server-side infrastructure work has already produced measurable wins in latency, reliability, memory usage, and compute efficiency for important services. Based out of OpenAI’s Bellevue office, we are a close-knit team that values in-person collaboration, urgency, craft, and impact. We build for other builders, and the best version of this team is one where every OpenAI product team can move faster because the experimentation and rollout layer is dependable, fast, and easy to use. About the Role We are l

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 Build the most advanced AI Meeting Notes product — and expand it into broader “AI data capture” features that help teams turn conversations into durable context, tasks, and knowledge. Our mission is to 10x the rate of business context & data that enters Notion — optimized for agents — so teams get superhuman memory across workstreams and customers. Notion workspaces that use AI Meeting Notes already enter 6x more data on a daily basis, so we’re well on our way. What You'll Achieve Ship end-to-end product experiences across capture → transcript → summary → follow-ups (full-stack ownership). Make meeting & data capture feel effortless and magical (e.g., speaker identification via audio waveforms, richer in-meeting UX, smarter organization). Improve summary quality that teams trust: structure, factuality, and citations that make downstream agents and humans more capable. Raise the bar on reliability & observability across the pipeline (SLOs, debugging workflows, incident response) for realtime systems. Build agentic meeting workflows that turn discussions into tasks, follow-ups, and organized knowledge — so “w

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake’s cloud spend is in billions of dollars per year. Hence, it is critical for us to govern and optimize our cloud spend, both for margins and long-term competitive advantage. Cloud Efficiency team’s charter is to build scalable products that enable governance, monitoring and optimization of cloud spend. Think of this as Observability for cloud costs and efficiency. The team’s vision is to “Transform cloud spend into a competitive advantage by empowering teams to continuously optimize the per-unit cost.” In order to improve the overall cloud efficiency (i.e. cost per unit), it is critical to build monitoring products that collate costs with other factors such as utilization, attribution, hardware performance and architecture. Hence, there is an opportunity to build a unified, self-serve cloud efficiency product across Snowflake, that delivers actionable, real-time efficiency datasets through streamlined user experiences. This will enable thousands of engineers at Snowflake and will elevate cloud efficiency at Snowflake for long-term success. When developing these solutions, we think about the problem end-to-end: how do we collect data from different stacks (e.g. costs from AWS, GCP, Azure and CPU, Memory, Utilization) across Snowflake reliably, how do we store it eff