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Design and implement high-performance TPU kernels to enhance AI model efficiency. Responsibilities include kernel optimization, debugging, and collaborating on system architecture.
OpenAI · 22d ago
The ChatGPT Learning team creates the next generation of learning experiences within ChatGPT. Millions of people use ChatGPT each week to explore concepts, practice skills, and work through challenges, making learning one of the platform’s largest consumer use cases.
The Connector Ecosystem team builds the platform and product experiences that let people extend ChatGPT and Codex. We work on plugins, skills, connectors, interactive apps, and open standards like the Model Context Protocol (MCP).
This team builds and operates the systems that enable OpenAI researchers to run reliable, scalable, and efficient research workflows.
Our engineering teams push the boundaries of what's possible, and we're looking for talented individuals to join us on this exciting journey.
Our Inference team brings OpenAI’s most capable research and technology to the world through our products. We empower consumers, enterprises and developers alike to use and access our state-of-the-art AI models, allowing them to do things that they’ve never been able to before.
The Platform Systems team at OpenAI operates at the intersection of cutting-edge AI and large-scale distributed systems. We build the engineering and research infrastructure required to train OpenAI’s flagship models on some of the world’s largest, custom-built supercomputers.
The Workload Networking team is responsible for the collective communication stack used in our largest training jobs.
Project leads at Mercor run and scale distinct data production businesses, each hiring and upskilling thousands of experts, while managing throughput and quality.
Some of the most valuable work on Mercor's platform is code —the tasks, problems, and solutions that train and evaluate the world's frontier coding models.
The Applied AI org builds the systems that turn human expertise into training data for frontier models, task pipelines, expert workflows, evaluation infrastructure, and the services that tie them together.
The Applied AI org builds the systems that turn human expertise into training data for frontier models, task pipelines, expert workflows, evaluation infrastructure, and the services that tie them together.
Compute Foundations builds the software that manages OpenAI’s GPU compute infrastructure across sites, data centers, and infrastructure providers, supporting model training and inference.
Frontier Systems Foundations, part of Compute Foundations at OpenAI, builds the systems software foundation that turns new compute infrastructure into reliable, usable capacity for frontier model training.
We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT.
As OpenAI continues to grow, we are looking for experienced, problem-solving engineers to ensure our systems scale. Our success depends on our ability to quickly iterate on products while also ensuring that they are performant and reliable.
Cloud Infrastructure builds the shared platforms behind ChatGPT and the OpenAI API. We work across engineering and product teams to make infrastructure reliable, secure and easier to use as OpenAI grows.
As an engineer within Fleet infrastructure, you will design, write, deploy, and operate infrastructure systems for model deployment and training on one of the world’s largest GPU fleet.
The Engineering Acceleration Delivery / Continuous Deployment team builds and operates the systems that safely ship OpenAI’s infrastructure and product code to production.
The Engineering Acceleration team designs, builds and maintains the foundational systems that engineers use to build ChatGPT and the API.
The Plugin Ecosystem team builds the platform and product experiences that let people extend ChatGPT and Codex. We work on plugins, skills, connectors, interactive apps, and open standards like the Model Context Protocol (MCP).
The Plugin Developer Platform team builds the APIs, SDKs, and tools that let people extend ChatGPT and Codex. We work on plugins, connectors, the Model Context Protocol (MCP), and interactive apps.
The Engineering Acceleration team builds and operates the foundational systems that engineers use to build, test, and ship ChatGPT, the API, and OpenAI's infrastructure.
Anthropic is seeking talented and experienced Infrastructure Engineers to join our team and support the development, scaling, and maintenance of our cutting-edge AI systems.
We collaborate closely with safety researchers and inference engineers to bring new classifiers and novel classes of ML defenses to production. We own the research → production transfer of new safety technologies that is on the critical path for every Claude model launch.
The Safeguards ML Sampling Path team builds and operates the production services that power Claude's safety systems.
Anthropic · 4mo ago
The Safeguards team is responsible for ensuring our models and products are developed and deployed safely.
This role focuses on developing cutting-edge AI systems with a mission to ensure safety and societal benefit. You'll work on technical challenges in a collaborative environment across key tech hubs.
Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models.
Perplexity · 16d ago
Build a self-serve compute platform. Design and own the systems that let inference engineers and researchers launch training jobs and operate inference services without managing GPU provisioning, cluster configuration, or provider-specific infrastructure. Operate the GPU fleet .
Research & Development. Post-train SOTA LLMs using the latest supervised and reinforcement learning techniques (SFT/DPO/GRPO). Leverage our rich query/answer dataset to scale model performance across Sonar, Deep Research, Comet, and Search products.
Perplexity · 7mo ago
We build and run the inference engine behind every Perplexity query and deploy dozens of model architectures at scale with tight latency and cost budgets. Our stack is Rust, Python, CUDA, and CuTe DSL - and we need another engineer to join us.
AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles.
Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors.
Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models.
The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models.
Life sciences is one of the clearest areas where advances in intelligence can meaningfully benefit the world at large.
Define architecture, standards, and deliver solutions end to end. You will lead builds across Node.js services, AI and agent workflows, and integrations with enterprise systems, owning quality and reliability.
The Infranomics team builds the software and data foundations that help OpenAI understand, plan, and improve the economics of its infrastructure.
The Physical Engineering team sits within OpenAI’s Enterprise Verticals organization.
San Francisco, CA +2
San Francisco, USA