Design Engineers Jobs

About the Team The ChatGPT Learning team focuses on building the next generation of learning experiences inside ChatGPT. Learning is already one of the largest consumer use cases on the platform, with millions of people each week using ChatGPT to understand concepts, practice skills, and get unstuck while learning. Our goal is to evolve ChatGPT from a place people go for one-off answers into a platform that helps people learn, grow, and make progress over time. We are exploring how AI can expand access to powerful learning tools for people everywhere—helping individuals better understand the world, build new skills, and pursue their goals. This team sits at the intersection of product engineering, design, AI research, and education, working to bring powerful learning experiences to a global audience. About the Role As a Full Stack Engineer on the ChatGPT Learning team, you will help design and build new product experiences that enable millions of people to learn with ChatGPT. You’ll work across the stack—from user-facing interfaces to backend services—to ship product features that make learning more intuitive, engaging, and effective. You’ll collaborate closely with researchers and platform teams to bring cutting-edge model capabilities into real-world products, helping translate advances in AI into experiences that people can use every day. We’re looking for engineers who enjoy building polished product experiences, operating with high ownership, and solving ambiguous problems that sit at the intersection of AI research and consumer software. This role is based in San Francisco or New York City. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. What You’ll Do Build end-to-end product experiences that help people learn with ChatGPT. Design and implement new multimodal capabilities that bring text, images, voice, and interactive interfaces into learning workflows. Develop scalable backend services and APIs t

About the Team 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. Our team develops core model training software and works deep in the stack - spanning collective communication, compute efficiency, parallelism strategies, fault tolerance, failure detection, and observability. The systems we build are foundational to OpenAI’s research velocity, enabling reliable, efficient training at frontier scale. We collaborate closely with researchers across the organization, continuously incorporating learnings from across OpenAI into the evolution of our training platform. About the Role As a Software Engineer, Platform Systems, you will design and build distributed systems that provide visibility into large-scale training workloads and help operate them reliably at scale. You’ll work on failure detection, tracing, and observability systems that identify slow or faulty nodes, surface performance bottlenecks, and help engineers understand and optimize massive distributed training jobs. This infrastructure is critical to operating OpenAI’s training stack and is actively evolving to support new use cases and increasingly complex workloads. This role sits at the core of our training infrastructure, blending systems engineering, performance analysis, and large-scale debugging. In This Role, You Will Design and build distributed failure detection, tracing, and profiling systems for large-scale AI training jobs Develop tooling to identify slow, faulty, or misbehaving nodes and provide actionable visibility into system behavior Improve observability, reliability, and performance across OpenAI’s training platform Debug and resolve issues in complex, high-throughput distributed systems Collaborate with systems, infrastructure, and research teams to evolve platform

About the Team GTM Growth Engineering builds AI-native products and systems that help OpenAI's go-to-market and B2B marketing organizations operate with greater speed, focus, and leverage. Our mandate is revenue leverage: products tied directly to pipeline quality, customer engagement, seller and marketer productivity, and the speed at which OpenAI can bring its technology to customers. We build the infrastructure and user experiences behind high-impact GTM workflows, including customer context, prioritization, routing, campaign execution, review surfaces, feedback loops, and measurement. Our work combines product craft, applied AI, reliable systems, and thoughtful operational design. About the Role We’re looking for a product-minded Software Engineer to build AI-powered products and full-stack experiences for GTM Growth Engineering. You will own meaningful product slices end to end, from user experience and frontend implementation to backend APIs, integrations, data models, instrumentation, and launch readiness. This is a role for engineers who want to build products that do real work in production. You will partner with Product, Design, Data Science, Sales, B2B Marketing, and operations teams to understand high-value workflows and ship systems that improve customer engagement, pipeline, conversion, and team productivity. The role is ideal for a strong product engineer who can move between product craft, systems engineering, applied AI, and measurable business outcomes. You should be excited to build from ambiguous problem statements, ship quickly, and improve products based on real user feedback. What You'll Do Build AI-powered products and workflows that help sales and B2B marketing teams identify opportunities, coordinate work, and engage customers more effectively. Own full-stack product experiences from prototype through launch, instrumentation, iteration, and production hardening. Design intuitive user journeys that combine polished interfaces, reliable servi

About the Team The Synthetic RL team develops reinforcement learning methods that leverage synthetic data, environments, and feedback to train and evaluate frontier AI models. The team explores approaches such as self-play, simulators, and other synthetic evaluations to push model capability, generalization, and alignment beyond what is possible with the current prevailing methodology. About the Role As a Research Scientist on the Synthetic RL team, you will develop novel reinforcement learning techniques that use synthetic environments and feedback to improve large-scale models. You’ll work closely with other researchers to design experiments, analyze learning dynamics, and translate research insights into training approaches used in production systems. We’re looking for researchers who enjoy working on open-ended problems, value fast iteration, and want their work to directly shape how frontier models are trained. 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: Research and develop reinforcement learning algorithms Design and run experiments to study training dynamics and model behavior at scale Collaborate with engineers and researchers to integrate successful approaches into model training pipelines You might thrive in this role if you: Have a strong background in reinforcement learning, machine learning research, or related fields Have strong engineering and statistical analysis skills Enjoy exploring new problem spaces where data, objectives, and evaluation are imperfect or evolving Are motivated by seeing research ideas influence real-world AI systems 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 our products. AI is an ex

About the Team The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time. About the Role We’re looking for engineers to build the infrastructure that powers Codex agents in production. This role focuses on the systems that let models safely execute code, interact with tools, complete long-running tasks, and operate reliably and efficiently at scale. You’ll design and operate the infrastructure behind sandboxed execution, orchestration, stateful workflows, app-server and SDK boundaries, and model rollouts. You’ll work at the intersection of distributed systems, developer tooling, and AI, building primitives that make Codex faster, safer, more reliable, and easier for the rest of the organization to build on. What You’ll Do Design and build execution environments for AI agents, including sandboxing, isolation, and reproducibility. Develop systems for agent orchestration across multi-step, tool-using workflows. Build infrastructure for running, testing, and debugging code generated by models. Create state and memory systems that allow agents to persist context across long-running tasks. Optimize tokens, latency, reliability, and cost across Codex’s production fleet. Support model rollouts, capacity planning, and the core tradeoffs between quality, speed, and economics to manage a fleet of frontier agents at scale. Build shared platform capabilities that unblock product teams, partner teams, and open source Codex. Yo

About the Team The Future of Computing Research team is an applied research team in the Consumer Devices group focused on developing new methods and models to support our vision as we advance forward in our mission of building AGI that benefits all of humanity. About the Role As a Technical Lead on the Future of Computing Research team, you will work together with both the best ML researchers in the world and the greatest design talent of our generation to push the frontier of model capabilities. This role is based in San Francisco, CA. We follow a hybrid model with 3 days a week in the office and offer relocation assistance to new employees. In this role, you will: Evaluate and select silicon platforms (GPUs, NPUs, and specialized accelerators) for on-device and edge deployment of OpenAI models. Work closely with research teams to co-design model architectures that meet real-world deployment constraints such as latency, memory, power, and bandwidth. Analyze and model system performance, identifying tradeoffs between model design, memory hierarchy, compute throughput, and hardware capabilities. Partner with hardware vendors and internal infrastructure teams to bring up new accelerators and ensure efficient execution of transformer workloads. Build and lead a team of engineers responsible for implementing the low-level inference stack, including kernel development and runtime systems. Run through the necessary walls to take nascent research capabilities and turn them into capabilities we can build on top of. You might thrive in this role if you: Have experience evaluating or deploying workloads on GPUs, NPUs, or other specialized accelerators. Understand the performance characteristics of transformer models, including attention, KV-cache behavior, and memory bandwidth requirements. Have designed or optimized high-performance compute systems, such as inference engines, distributed runtimes, or hardware-aware ML pipelines. Have experience building or leading teams work

About the Team The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time. About the Role We’re looking for applied AI engineers to help bring Codex agents from impressive demos to dependable tools. This role is about improving agent performance on real software engineering tasks and closing the gap between research capability and real-world usefulness. You’ll work closely with research, infrastructure, and product to ensure agents are not just powerful, but useful, steerable, and reliable in practice. The job is not only to improve model behavior in isolation, but to turn those improvements into measurable gains in solve rate, usefulness, and economic value for users. What You’ll Do Design and iterate on agent behaviors across real-world coding tasks and long-horizon workflows. Work closely with research to develop and run evals to measure agent performance, regressions, failure modes, and edge cases. Improve performance through prompting, tool-use strategies, context construction, and model-facing experimentation. Analyze failures in production and systematically improve robustness and reliability. Build feedback loops and data systems that get better real-task data into evaluation and research. Work with product teams to shape user-facing agent experiences and the interfaces the agent depends on. Help define what “good” looks like for agents completing complex tasks end-to-end. You Might Be a Good Fit If You Ha

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who are you? We are seeking a Software Engineer to join the Ema team. You are passionate about designing and developing maintainable software applications. You are a creative problem solver who thrives in ambiguity and can make abstract problems concrete. Most importantly, you are excited to be part of a mission-oriented, fast-paced, high-growth startup that can create a lasting impact. You Will: Design, develop, and implement exceptional user interfaces for web applications, using modern web technologies such as HTML, CSS, and JavaScript. Collaborate closely with product managers, UX designers, and other stakeholders to gather requirements, own the user experience, develop wireframes, and create high-fidelity prototypes. Develop and maintain API integrations, ensuring seamless communication between front-end and back-end systems, as well as with third-party services. Build, test, and deploy web applications using a variety of web development frameworks, such as React, Angular, Vue.js, or Next.js. Troubleshoot and resolve UI-related issues, guaranteeing a consistent and optimal user experience across multiple platforms and devices. Build end-to-end writing clean, maintainable, and

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. In this role, You Will: Design, develop, and implement exceptional user interfaces for web applications using modern web technologies such as HTML, CSS, and JavaScript. Collaborate closely with product managers, UX designers, and other stakeholders to gather requirements, own the user experience, develop wireframes, and create high-fidelity prototypes. Develop and maintain API integrations, ensuring seamless communication between front-end and back-end systems using React and gRPC. Contribute to back-end development with a focus on creating robust APIs and ensuring smooth communication between the front-end and server using technologies like Node.js or Python. Build, test, and deploy full-stack web applications using React and gRPC, while ensuring responsiveness, performance, and scalability. Optimize web applications for performance, accessibility, and SEO best practices. Troubleshoot and resolve UI and back-end related issues, ensuring a consistent and optimal user experience across multiple platforms and devices. Write clean, maintainable, and well-documented code adhering to established coding standards, and deploy/debug using platforms like Vercel. Ideally You'd Have: Bachelor

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who you are We are seeking an experienced DevOps Engineer to join our growing team and play a pivotal role in designing and building our platform and infrastructure as we continue to scale our product and user base. As a part of our team, you will be working in a dynamic, fast-paced environment to ensure the reliability, scalability, and performance of our systems, while focusing on service architecture and deployment, query optimization, distributed systems, data and machine learning infrastructure, and security and authentication. Most importantly, you are excited to be part of a mission-oriented, fast-paced, high-growth startup that can create a lasting impact. You will: Partner with product teams to architect, design, and build the foundational infrastructure for our products. Design, develop, and deploy highly available and scalable Multi-tenant SaaS solutions on any one of the public cloud networks like AWS, Azure and GCP. Leverage technologies such as Kubernetes, Helm, Terraform, and Istio to achieve infrastructure resilience. Drive the automation of infrastructure tasks, from provisioning to configuration management and deployment, utilizing tools like Terraform, Ansible, a

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who you are You are an experienced Platform Engineer who owns backend infrastructure end to end. You design multi-tenant, microservices-based systems that other engineering teams build on, and you make deliberate architectural tradeoffs around consistency, latency, scale, and cost. You are comfortable going deep — service mesh internals, database internals, distributed-systems failure modes — and equally comfortable defining the reliability and security contracts an enterprise AI platform depends on. Responsibilities Design, own, and evolve scalable microservices architectures on Kubernetes across GCP, Azure, and AWS, including multi-tenant isolation (namespaces, network policies, per-tenant resource quotas and RBAC). Build core platform and data-plane components in Golang and Python — data ingestion, knowledge-base indexing and vector/graph search, application connectivity, workflow automation, and ML operations — against explicit latency and throughput SLOs. Own service-to-service communication: gRPC/protobuf API contracts, service mesh (Istio/Linkerd), load balancing, retries, timeouts, and circuit breaking. Make and document architectural tradeoffs — partitioning/sharding strat

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Role Overview & Key Responsibilities This is a high-leverage leadership role that spans architecture, execution, and org-building, and will shape the direction of our AI / ML initiatives at Ema. We are seeking an AI / ML technical leader who can take a vision and build it. As a Principal ML Engineer at Ema, you will be a senior technical leader responsible for shaping the machine learning roadmap, architecting large-scale ML systems, driving innovation, and ensuring our mixture of expert models (LLM + SLM + Custom Model) is accurate and performant at scale. You will collaborate across teams (research, product, infra, data, etc.), mentor senior engineers, and influence strategy and execution at company-wide levels. Responsibilities Lead the technical direction of GenAI and agentic ML systems that power enterprise-grade AI agents — spanning reasoning, retrieval, tool use, and integrations across various SaaS products. Architect, design, and implement scalable production pipelines for model training, fine-tuning, retrieval (RAG), agent orchestration, and evaluation — ensuring robustness, latency efficiency, and continuous learning. Define and own the multi-year ML roadmap for GenA

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. The Role You'll be an engineer who builds AI agents in production, sitting close to the customers who depend on them. This is a full-stack engineering job with an unusually short distance between your code and someone's actual workday. You'll write Go and Python, design schemas, build evals, and present your solution to a senior executive at an enterprise - often in the same week. What You'll Do Design and ship production agents. You'll build agents that are mission-critical from day one: embedded in Teams, Slack, intranets, voice lines, and email, taking real actions against SAP, ServiceNow, Workday, and a long tail of systems nobody has heard of. These run at enterprise volume under enterprise scrutiny. Own the full lifecycle. Discovery, build, eval, launch, and the unglamorous months afterward where an agent goes from good to genuinely reliable. Work directly with the people whose problem it is. You'll sit with leaders at global enterprises, extract the process from their heads, and decide what should be an agent, what should be a workflow, and what should stay human. Push your work back into the platform. The best patterns you find in the field become part of Ema's core product

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who You Are The AI Implementation Engineer owns the technical delivery and stabilization of Ema's agentic AI solutions in customer environments — from commitment through production rollout and steady state. This is a hands-on, post-sales, customer-facing engineering role: you build, you deliver, and you are the technical anchor the customer leans on. You are equally comfortable writing production code, debugging an integration the night before a go-live, walking a customer's VP of Operations through an architecture decision and translating a messy business problem into a feasible agentic workflow. You thrive in ambiguity, make abstract problems concrete, and reduce chaos rather than amplify it when things go wrong. You'll work closely with Value Engineering, Product, Engineering, Infrastructure, and the customer's IT and business teams to prove that agentic AI can be implemented responsibly — not heroically. What You'll Work On End-to-End AI Delivery Ownership Own technical delivery from design alignment through production rollout and Stabilization Configure, extend, and integrate Ema's agentic AI platform to meet customer requirements Ensure solutions align with Ema's agentic arch

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. In this role, you will: Collaborate with the sales leadership to understand customer requirements and enable technical solutions deployment based on customer needs. Develop an in-depth understanding of Ema’s technology and underlying architectures Deliver compelling product demonstrations tailored to the specific needs of potential customers, showcasing key features and benefits. Work closely with customers to execute successful PoCs, demonstrating the feasibility and value of Ema in their environment. Position yourself as a Trusted Advisor to key customer stakeholders with a focus on achieving their desired Business Outcomes. Collaborate with customers to design and architect solutions that align with their business goals, ensuring seamless integration with existing systems. Drive project teams towards common goals of accelerating the adoption of Ema’s solutions. Demonstrate and communicate the value of Ema’s solution throughout the engagement, from demo to proof of concept to running workshops, design sessions and implementation with customers and stakeholders. Help take Ema’s solution from POC to production. Understand customers cloud/on-prem environment and their unique needs f