About PostHog PostHog is your product’s context layer. It ingests and stores your analytics, errors, replays, and business data so you and your agents can query and act on it. We launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products, including: A suite of analytics and observability tools, including product analytics , replay vision , AI observability , and error tracking PostHog MCP for users and their agents to query and act on their product and business data Data warehouse so users can query product and customer data together using custom SQL insights. We are: Product-led . More than 500K organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not now? We want to build a lot of products; we can't do that shipping at a normal pace. We've built the company around small teams – autonomous, highly-efficient gro
Role overview
Job description
About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. The Compute team works on the design of our AI supercomputers, doing everything from workload modeling to influencing accelerator design. We’re leaning into our partnerships to make system and data center co-design an integral part of this process, and are looking for engineers to design AI supercomputers solutions for data
…What they are looking for
Skills & requirements
Qualification
You’ll translate operating conditions and service-life goals into reliability requirements, design and execute qualification tests, and drive failure analysis and corrective-action verification from development through production and field deployment; Own reliability qualification plans from new product introduction through production, defining test coverage, representative configurations, sample sizes, stress conditions, duration, pass/fail criteria, and exit evidence at each assembly level; Identify gaps between component qualification and the stresses encountered in the integrated system or rack; Present qualification results, unresolved failure modes, and residual risk at design and release reviews
Department · Scaling
Hiring company
OpenAI
FONDER L'INNOVATION (depuis 1984) Partie I [le début n'avait même pas 2 fin.s] : The Book of.f MandaloriÂn.e Studio d'innovation ouvert.e (Open Innovation) issu de la fusion des activités du bureau d'étude (BE) de la marque 2 fabrique OPENAI (Open Ahead Inspiration) créée initialement à Genève (CH)
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