Frontier Ux Engineer Jobs

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team The Biohub is a group of nonprofit research institutes that bring together scientists, engineers, and physicians with the goal of pursuing grand scientific challenges on 10- to 15-year time horizons. The Biohub focuses on understanding underlying mechanisms of disease and developing new technologies that will lead to actionable diagnostics and effective therapies. Our Vision We pursue large scientific challenges that cannot be pursued in conventional environments We enable individual investigators to pursue their riskiest and most innovative ideas The technologies developed at the Biohub facilitate research by scientists and clinicians at our home institutions and beyond Diversity of thought, ideas, and perspectives are at the heart of Biohub and enable disruptive innovation and scholarly excellence. We are committed to cultivating an organization where all colleagues feel inspired and know their work makes an important contribution. The Opportunity The Biohub Chicago is seeking an exceptional Computational Biologist, Spatiotemporal Multi-Omics to join our growing team. We are looking for a creative and collaborative bioinformatics researcher who is excited to build the analytical foundation for our spatiotemporal multi-omics technology platform. What You'll Do Develop data analysis workflows for spatiotemporal and multi-omics datasets. Build visualization tools that enable exploration and interpretation of complex biological data across space and time. Integrate proteo

About the team The AI Deployment Engineering team works closely with frontier startups. We are trusted advisors to, and thought partners with, startups to ensure that OpenAI’s technology is deployed safely and effectively, whilst also partnering with engineering, research, and product to turn those insights into evaluation systems, product improvements, and better model behavior. This team sits at the intersection of customer reality and model quality. We combine hands-on technical depth with strong product judgment, helping translate complex, high-value use cases into clear signals that can improve both the customer experience and the underlying systems. About the role We are seeking a technically proficient, product-minded engineer to help push the frontier of advanced AI with our strategic startup customers. You'll work with some of the most exciting AI startups in the world, helping them optimize their own systems and turning those learnings into durable improvements across OpenAI’s research and products. You will partner deeply on complex workflows, identify the gaps that matter, and help transform those gaps into reproducible evaluations, technical insights - helping shape OpenAI's research and product direction. This role is well suited to engineers who are equally comfortable debugging a workflow, iterating on prompts or agents, designing evaluations, and collaborating across research and product. You should be excited by ambiguous, high-impact problems and motivated by the opportunity to shape how advanced AI systems improve in practice. This role is based in London. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. In this role, you will: Work directly with strategic startup customers to understand critical workflows, uncover failure modes, and identify high-impact opportunities for improvement. Prototype and iterate on prompts, agents, and workflow designs to better understand system behavior and unlock customer

About the team The AI Deployment Engineering team works closely with frontier startups. We are trusted advisors to, and thought partners with, startups to ensure that OpenAI’s technology is deployed safely and effectively, whilst also partnering with engineering, research, and product to turn those insights into evaluation systems, product improvements, and better model behavior. This team sits at the intersection of customer reality and model quality. We combine hands-on technical depth with strong product judgment, helping translate complex, high-value use cases into clear signals that can improve both the customer experience and the underlying systems. This role is based in Paris. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. We require fluency in French for this role. About the role We are seeking a technically proficient, product-minded engineer to help push the frontier of advanced AI with our strategic startup customers. You'll work with some of the most exciting AI startups in the world, helping them optimize their own systems and turning those learnings into durable improvements across OpenAI’s research and products. You will partner deeply on complex workflows, identify the gaps that matter, and help transform those gaps into reproducible evaluations, technical insights - helping shape OpenAI's research and product direction. This role is well suited to engineers who are equally comfortable debugging a workflow, iterating on prompts or agents, designing evaluations, and collaborating across research and product. You should be excited by ambiguous, high-impact problems and motivated by the opportunity to shape how advanced AI systems improve in practice. In this role, you will: Work directly with strategic startup customers to understand critical workflows, uncover failure modes, and identify high-impact opportunities for improvement. Prototype and iterate on prompts, agents, and workflow designs to better unde

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment. Our research spans: Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond. Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science Imaging foundation models trained across the world's largest microscopy datasets Reasoning and agentic systems that connect frontier LLMs with biological foundation models Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled Join Our Team! As a Research Engineer, you'll build the models and systems that define what AI can do in biology: foundation models, reasoning, reinforcement learning, and multi-agent systems at frontier scale. What You'll Do Build on and advance the AI systems at th

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment. Our research spans: Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond. Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science Imaging foundation models trained across the world's largest microscopy datasets Reasoning and agentic systems that connect frontier LLMs with biological foundation models Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled Join Our Team! As a Research Scientist, you'll build the models and systems that define what AI can do in biology: foundation models, reasoning, reinforcement learning, and multi-agent systems at frontier scale. What You'll Do Build on and advance the AI systems at t

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment. Our research spans: Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond. Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science Imaging foundation models trained across the world's largest microscopy datasets Reasoning and agentic systems that connect frontier LLMs with biological foundation models Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled Join Our Team! As a Research Scientist, you'll build the models and systems that define what AI can do in biology: foundation models, reasoning, reinforcement learning, and multi-agent systems at frontier scale. What You'll Do Build on and advance the AI systems at t

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment. Our research spans: Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond. Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science Imaging foundation models trained across the world's largest microscopy datasets Reasoning and agentic systems that connect frontier LLMs with biological foundation models Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled Join Our Team! As a Research Engineer, you'll build the models and systems that define what AI can do in biology: foundation models, reasoning, reinforcement learning, and multi-agent systems at frontier scale. What You'll Do Build on and advance the AI systems at th

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team The AI Cluster Production Engineering team is part of the AI Compute Platform organization at Biohub, a non-profit research lab committed to open science and open-source AI. We own the design, operation, and reliability of large-scale multi-GPU AI clusters that power frontier AI biology research: protein language models, genomic foundation models, and scientific reasoning systems built to be shared, not monetized. Our clusters run Slurm on Kubernetes infrastructure and support everything from day-to-day AI researcher workflows to multi-node hero training runs at thousands of GPUs. The team works at the intersection of AI tooling, distributed systems, HPC, and frontier AI, debugging deep AI infrastructure problems and building AI systems critical to the entire AI organization. The Opportunity CZ Biohub's mission is to cure or prevent all human disease. Achieving that requires training frontier-scale AI biology models, and that demands reliable, high-performance compute infrastructure. This is production engineering work at a frontier AI lab, with the twist that the mission is biology and the science is open. You'll keep GPU clusters running at high utilization, debug the toughest distributed systems failures, and build the operational foundations for scaling to multi-thousand GPU hero runs. The technical problems are genuinely hard (e.g., multi-node distributed training, InfiniBand fabrics, large-scale storage, Slurm at scale) inside an organization where the work is aimed at helping peop

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team Biohub is a 501(c)(3) biomedical research organization building the first large-scale scientific initiative combining frontier AI with frontier biology to solve disease. We build the technology to help scientists around the world use AI-powered biology to study how cells operate, organize, and work as part of systems to understand why disease happens and how to correct it. With our compute capacity, AI research and engineering, and state-of-the-art technology for measuring, imaging, and programming biology, we are enabling scientists worldwide to use AI-powered biology to advance our understanding of human health. The Opportunity The role is part of the Data Engineering team, which focuses on owning the strategy, sourcing and implementation for data supporting AI research and development. Our goal is to maximize the speed, agility, and capability of biological AI research by connecting public data resources and Biohub's experimental platforms to AI systems. The data that trains biological frontier models comes in dozens of modalities (sequences, images, spatial coordinates, time series, molecular structures, metadata, publication artifacts) each with its own noise characteristics, biases, and information content. The question of how to represent this data for learning is one of the most important open problems in biological AI. As a Senior Staff Data Engineer at Biohub, you'll be designing systems that ingest data from public repositories, transform heterogeneous biological formats into AI-rea

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 You'll own the quality bar for Notion AI products. You’ll work with product and engineering teams to build systems to define what “good” looks like, measure our progress, and drive changes to deliver reliable and high-quality AI experiences. Your work directly shapes how Notion's AI products behave for millions of users. This isn't a traditional software engineering role. It’s an art & science role . You won't spend your days writing code. Instead, you'll focus on understanding and shaping how our AI products behave through context engineering, designing evaluation systems, and analyzing data. This team sits in our AI engineering team, working directly with engineering, product, design, and data. This role is a unique blend of ops, strategy, and product thinking. Day to day, you'll live in production data, ship prompt fixes, run evals and, in effect, shape our quality strategy. As part of that you'll shape Notion's model strategy and work directly with frontier AI labs (OpenAI, Anthropic, Google) to evaluate and launch new models. We're looking for problem-seeking generalists interested in 0 → 1 : curious people wi

About the Team The Codex Research team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of the Codex Research team, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measu

About the Team Safety Systems manages the complete lifecycle of safety efforts for OpenAI’s frontier models, ensuring our models are deployed responsibly and have a positive impact on society. Our work spans diverse research and engineering initiatives—from system-level safeguards and model training to evaluation and red-teaming—all aimed at mitigating misuse, misalignment, and maintaining our high bar for safety. We lead OpenAI's commitment to developing and deploying safe Artificial General Intelligence (AGI), fostering a culture of trust, responsibility, and transparency. Our goal is to continuously learn from deployments, distribute AI’s benefits widely, and ensure that powerful tools remain aligned with human values and safety considerations. Within Safety Systems, the Model Policy team works to ensure that frontier models behave safely and reliably in real-world environments by designing policies that define safe model behavior. We've had several relevant publications, including: Safety at every step OpenAI GPT6 System Card OpenAI Model Spec About the Role We’re hiring a Model Policy Manager to shape model behavior for U.S. government use, with a focus on national security applications. You’ll define nuanced policies and translate them into training and evaluation criteria, helping models navigate high-stakes scenarios while preserving their usefulness and capabilities. In this role, you’ll: Develop model policies that guide safe and useful behavior. Build evaluations, identify policy gaps and model failures, and use findings to improve policies and training. Work with research, engineering, and domain experts to support safe, reliable deployment. You might thrive in this role if you: Bring relevant experience in AI safety, policy, or risk assessment. Have strong judgment and can turn complex safety questions into clear, practical policies. Have the technical fluency to work hands-on with model data and evaluations. Are motivated by OpenAI’s mission and the re

About the Team OpenAI's Compute organization builds and operates the infrastructure that powers frontier AI training and inference. Our data center engineering teams develop the technical standards and infrastructure required to deploy compute at unprecedented scale across both self-built and partner-operated environments. We work across civil, structural, mechanical, electrical, construction, and infrastructure delivery to develop data center designs that are reliable, scalable, and optimized for speed. About the Role We are seeking a Data Center Design Manager to coordinate the design and delivery of infrastructure for large-scale AI deployments. You will bring engineering disciplines and external design partners together to translate infrastructure requirements into coordinated, buildable design packages. You will manage design milestones, resolve cross-discipline interfaces, and keep technical decisions aligned with project requirements. Working with engineering, construction, commissioning, operations, and hardware teams, you will help preserve design intent from early planning through construction and turnover. The focus is design execution, technical coordination, and clear ownership of design decisions. Key Responsibilities Manage design scope, deliverables, milestones, and dependencies from concept development through detailed design and construction support. Coordinate civil, structural, architectural, mechanical, electrical, controls, and physical network interfaces across data center buildings and campuses. Translate owner and hardware requirements into coordinated design criteria, working with discipline leads to resolve gaps and competing requirements. Lead multidisciplinary design reviews; track comments, decisions, technical risks, and actions through resolution before design release. Evaluate design changes with engineering and delivery partners, making impacts on reliability, safety, cost, schedule, and maintainability clear. Coordinate external ar

About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. For software engineering organizations, this means helping customers adopt Codex and other OpenAI capabilities across the software development lifecycle—transforming how teams plan, build, test, review, and deliver software. We work directly with engineering leaders and hands-on developers to identify high-value opportunities, design and implement AI-powered development workflows, and scale what works across engineering organizations. We turn lessons from these deployments into better products, reusable architectures, and technical patterns that help developers everywhere get more value from Codex. About the Role As an Applied AI Engineer focused on Codex, you will partner directly with leading engineering organizations to design, build, and deploy AI systems that transform how software is developed. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from workflow and use-case selection through prototyping, evaluation, production rollout, and scaled adoption. You will work alongside engineering teams to build advanced AI coding workflows, integrations, automations, and evaluation systems—often using Codex itself as part of your development process. You will help customers make technical decisions involving model behavior, agentic workflows, developer environments, security, reliability, evaluation, and operational readiness, while ensuring deployments translate into measurable improvements in engineering productivity and software delivery. You will work closely with OpenAI Product, Research, Engineering, Security, Sales, and the broader Codex organization, translating real-world deployment experience into high-signal product and model feedback. Success is measured by production systems, sustained developer adoption, and meaningful improvements to how

About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. For software engineering organizations, this means helping customers adopt Codex and other OpenAI capabilities across the software development lifecycle—transforming how teams plan, build, test, review, and deliver software. We work directly with engineering leaders and hands-on developers to identify high-value opportunities, design and implement AI-powered development workflows, and scale what works across engineering organizations. We turn lessons from these deployments into better products, reusable architectures, and technical patterns that help developers everywhere get more value from Codex. About the Role As an Applied AI Engineer focused on Codex, you will partner directly with leading engineering organizations to design, build, and deploy AI systems that transform how software is developed. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from workflow and use-case selection through prototyping, evaluation, production rollout, and scaled adoption. You will work alongside engineering teams to build advanced AI coding workflows, integrations, automations, and evaluation systems—often using Codex itself as part of your development process. You will help customers make technical decisions involving model behavior, agentic workflows, developer environments, security, reliability, evaluation, and operational readiness, while ensuring deployments translate into measurable improvements in engineering productivity and software delivery. You will work closely with OpenAI Product, Research, Engineering, Security, Sales, and the broader Codex organization, translating real-world deployment experience into high-signal product and model feedback. Success is measured by production systems, sustained developer adoption, and meaningful improvements to how