Reliable Bike Transport Services In Delhi in United States

The ChatGPT Finances team builds experiences that help people connect their financial accounts, understand their financial picture, and ask useful questions about their finances through ChatGPT. Our work spans account connectivity, data ingestion, dashboards, personalized insights, and conversational experiences. We collaborate across product, design, research, infrastructure, security, and data integrations to make complex financial information understandable and actionable. This is an early and ambitious product area with a substantial roadmap. We are looking for engineers who want to shape both the first user experiences and the durable systems required to earn and keep users’ trust. About the role We’re looking for full-stack product engineers to build and scale ChatGPT Finances. You will own features across the stack—from polished frontend experiences to the APIs, services, and data models that power them. This role is well suited to engineers who combine strong product judgment with broad technical depth. You should care about how quickly users can understand their financial lives, how reliably data moves through the system, and how AI can answer financial questions in a grounded, transparent, and useful way. You will work closely with product, design, research, infrastructure, security, and data integration teams to take ideas from early prototypes to reliable production experiences. In this role, you will Own full-stack product features from user experience and frontend implementation through backend services, data models, deployment, and observability. Build polished, accessible, and performant interfaces for account connection, dashboards, insights, and conversational workflows. Design APIs and backend systems that safely ingest, normalize, and serve financial data. Build resilient integrations that handle synchronization, data freshness, partial failures, permissions, and user consent. Bring new AI capabilities into production while prioritizing grounding

About the Team Security is at the foundation of OpenAI's mission to ensure that artificial general intelligence benefits all of humanity. The Identity Infrastructure Engineering team sits at the core of this effort, designing and building the identity and access management solutions that protect model weights, customer data, and critical systems across multiple cloud environments. The team partners across OpenAI, including Applied Engineering, Research, IT, Security, Infrastructure, and Engineering, to provide secure and scalable platforms for identity, access management, permissioning, orchestration, and safe AI research. About the Role We’re looking for an engineering leader to lead Identity Infrastructure Engineering, the team building the systems that govern and scale access across OpenAI’s research, engineering, and internal platforms. This role sits at the center of cloud infrastructure, identity, software engineering, and security-critical operations. You’ll lead engineers building control planes, policy systems, workload and agent authorization patterns, infrastructure-as-code, and operational foundations that help OpenAI move quickly while keeping access reliable, auditable, least-privileged, and safe under failure. The ideal candidate has led teams responsible for large-scale, mission-critical infrastructure. They can go deep into code and architecture when needed, while giving engineers and technical leads the clarity and ownership to do their best work. They set technical direction, grow strong teams, make durable architecture decisions, and turn ambiguous 0-to-1 problems into platforms OpenAI can trust and build on for years. In this role, you will: Build and lead a high-performing Identity Infrastructure team, going deep enough technically to set direction while empowering the team to own delivery. Define the strategy for identity platform as the policy plane for access across people, agents, workloads, services, clouds, and internal systems. Scale Acc

Join the engineering teams that bring OpenAI’s ideas safely to the world!! The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role We’re building the observability product for OpenAI—from scalable infrastructure to a rich, AI-powered UI. Our systems ingest over petabytes of logs and billions of time series metrics across our fleet. We're now layering intelligence on top—think agents that summarize SEVs, auto-generate dashboards, or help engineers debug through notebook-like UIs. We’re hiring software engineers across the stack—infra, backend, and product. You’ll join a small, gritty team building both foundational infra and novel internal tools to make OpenAI's production systems reliable, performant, and observable. What You’ll Do Own core observability infrastructure, including distributed logging, time series, and trace storage Build AI-native tools that help engineers detect, understand, and resolve issues autonomously. Contribute to UI experiences like dashboards, notebooking, or interactive debugging Collaborate closely with engineers, researchers, user ops, and other teams across the company to build the next generation observability product You Might Be a Fit If You: Have operated large-scale distributed systems in production. ( especially logging systems or some other time series databases) Thrive in ambiguous environments and roll up your sleeves to solve unscoped problems. Have full-stack chops or product sensibilities—you're excited to build real tools people use. Have strong fundamentals in systems, networking, and cloud infra (Kubernetes, AWS, etc). Bonus : built or contributed to observability systems (e.g. Prometheus, OpenTelemetry, etc). Why This Team We’re b

About the Team The Cooperative AI team is scaling to devices and embedded operations and user experiences. Our model-powered scaled workforce and knowledge system are moving on to the edge and powering our devices and edge experiences. By leveraging OpenAI’s state-of-the-art models and technologies, in production and in the lab, we develop systems that reason and work autonomously with customers and with our workforce responsible for operational work. We carry real workloads for critical systems across finance, sales, customer support, integrity, product insights, internal operations, and now devices to drive insights into product and industry. We partner closely with internal teams and external customers globally, operating in a hyper-fast feedback loop where many of our users are just a few steps away. This proximity allows us to iterate quickly, validate impact in real time, and accelerate industry impacting learnings and systems builds. We are a highly multidisciplinary, self-contained team focused on transforming the workplace via smart systems, knowledge, scalable and reliable primitives that apply world-class AI capabilities across domains. Our mission is to learn fast and transform how humans collaborate with AI at scale. About the Role We are looking for a Technical Lead Manager to lead a team of engineers building AI-native embedded experiences and operations-forward systems. In this role, you will perform both hands-on technical leadership and small team management. You will drive business outcomes, architecture and technical strategy for complex systems, contribute directly to implementation, and help grow a high-performing team. You will work closely with internal stakeholders to understand operational challenges, identify high-leverage opportunities for automation, and deliver solutions that create measurable impact. This role is ideal for someone who enjoys moving between technical design, coding, mentoring engineers, and working directly with users t

About the Team The Cybersecurity Products team builds products at the frontier of AI and cybersecurity. Our work includes Codex Security and related cyber products that turn advances in model capability into dependable tools for defenders. We help teams find, validate, and remediate vulnerabilities, continuously improve the security of software, and test AI-powered applications before they reach production. About the Role As a Full Stack Software Engineer, you will build the product experiences and systems that make AI-powered security useful in real engineering environments. You will work across web surfaces, APIs, orchestration, data models, and integrations to help security and engineering teams move from a codebase or application to evidence-backed findings, prioritized remediation, and revalidation. You will collaborate closely with product engineers, security researchers, and customer-facing teams. The work spans fast-moving product development and hard systems problems: long-running workflows, large repositories, sensitive data, reliability, observability, and a high bar for earning user trust. 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: Build end-to-end workflows for vulnerability discovery, security scanning, red teaming, findings review, remediation, and reruns. Design and operate backend services for long-running security work, including APIs, asynchronous orchestration, durable state, and integrations with developer workflows. Make complex security results actionable through clear product surfaces, strong evidence, thoughtful prioritization, and reliable reporting. Partner with security researchers, product teams, and users to evaluate quality, reduce noise, improve coverage, and ship safely. You might thrive in this role if you: Have experience shipping production full-stack products across modern web frontends and backend s

About the Team OpenAI's mission is to ensure that artificial general intelligence benefits all of humanity. The Consumer Devices team is building a new generation of AI-powered products that seamlessly integrate hardware and software to create intuitive, transformative experiences. We bring together experts across embedded systems, machine learning, hardware, design, and product engineering to develop products at the intersection of AI and consumer technology. About the Role OpenAI is seeking a System Performance Engineer to profile, benchmark, and optimize performance across our embedded hardware products. In this role, you will work across operating systems, applications, camera and vision, graphics, and platform teams to define product KPIs, build performance tooling, and drive optimizations from early lab characterization through product launch and real-world usage. You will help establish the performance standards that shape the user experience of our products, ensuring they remain responsive, efficient, and reliable throughout their lifecycle. This role requires deep expertise in embedded or high-performance systems, strong operating systems fundamentals, and hands-on experience debugging under tight latency, power, and memory constraints. This role is based in San Francisco, CA. We use a hybrid work model of four days per week in the office and one day working remotely. Relocation assistance is available for new hires. In this role, you will: Develop system performance benchmarks, methodologies, and policies to evaluate end-to-end product behavior. Profile and analyze performance across key product use cases and workloads using custom and industry-standard profiling tools. Partner closely with engineering teams to identify bottlenecks and drive performance optimizations across the software stack. Define high-level product KPIs and establish measurement frameworks to measure launch readiness and monitor performance throughout the product lifecycle. Measure, re

About the Team The Personalization-Memory team, within OpenAI's broader Personal AGI organization, is focused on developing agents that can learn from prior interactions in order to become more helpful and efficient over time. We build general-purpose memory and personalization capabilities that transfer across ChatGPT and other agentic products, and we collaborate with applied engineering on the product surfaces that allow users to interact with memory. About the Role As a Research Engineer / Research Scientist on the Personalization-Memory team, you will research and develop improvements to memory usage and personalization in OpenAI's frontier models. Our team works on reinforcement learning, dataset creation, evaluations, and other post-training methods. We partner closely with research and product teams across the company to realize the vision of a truly personalized ChatGPT. We're looking for individuals who have a background in frontier model post-training, are able to iterate quickly, and who are passionate about product-driven research. 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: Own and pursue a research agenda for improving memory use and personalization in frontier models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. Collaborate closely with the research and product teams to influence the shape of technical solutions in the product. You might thrive in this role if you: Are passionate about personalization and building personalized assistants. Have experience working with user signals and human data to turn feedback into reliable signals for training and evaluation. Have a deep understanding of frontier model post-training and machine learning applications. Value principled approaches and research craftsmanship. Are comfortable diving into a lar

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Identity Infrastructure Engineering team sits at the core of this effort, designing and building the identity and access management solutions that protect our model weights, customer data, and critical systems across multiple cloud environments. We partner with teams across OpenAI—Applied Engineering, Research, IT, and Security—to provide a secure and scalable platform for permissioning, orchestration, and innovative AI research. About the Role We’re looking for a Staff+ Software Engineer to help build and evolve the identity infrastructure that supports OpenAI’s research, engineering, and internal platforms. This role sits at the intersection of cloud infrastructure, identity systems, and software engineering. You’ll work across production systems, infrastructure-as-code, cloud control planes, identity providers, and operational infrastructure to build secure, scalable, and reliable systems used broadly across the company. The ideal candidate has experience building and operating large-scale, mission-critical systems with strong reliability and security requirements, and is comfortable writing production code, designing distributed systems, and driving ambiguous projects from 0 to 1 while building the operational rigor needed to run critical infrastructure over time. In this role, you will: Lead the architecture, development, and operation of identity infrastructure that spans cloud platforms, internal systems, and critical engineering services. Design and evolve systems for authentication, authorization, access governance, auditability, and policy enforcement with a strong focus on reliability, scalability, and secure-by-default design. Build foundational infrastructure and platform capabilities that are broadly used across engineering, research, and security teams. Improve the reliability, observability, performance, and op

About the Team Business Systems / Enterprise Platform Technology builds the internal systems, data foundations, workflow infrastructure, and enterprise platforms that help OpenAI operate at scale. The EPT AI Pod builds AI-native internal apps, MCP connectors, multi-agent workflows, and reusable platform capabilities across Finance, People, and GTM. About the Role As an Enterprise Applied AI Engineer, you will build internal apps for enterprise operations and the shared platform components those apps run on. This includes MCP connectors, multi-agent orchestration, data architecture, evals, monitoring, auditability, and governance. We’re looking for a hands-on engineer who is strong in Python, system design, enterprise integrations, data architecture, and applied AI systems. You should be excited to turn ambiguous business workflows into reliable internal products and shared infrastructure. In this role, you will: • Build internal apps for enterprise operations across Finance, People, and GTM • Build MCP connectors and enterprise integrations with strong auth, permissions, idempotency, retries, and rate-limit handling • Design end-to-end multi-agent workflows with tool routing, human approvals, audit trails, and safe action boundaries • Design data architecture for operational AI systems, including ingestion, schemas, quality checks, lineage, and governance • Build evals, monitoring, metrics, and regression tests for agentic workflows • Create reusable infrastructure, patterns, and components that other enterprise teams can build on • Partner with system owners and business owners to turn messy enterprise workflows into reliable internal products You might thrive in this role if you: • Have strong Python engineering skills for backend services, MCP connectors, agent/tool workflows, eval harnesses, and data ingestion jobs • Have strong system design skills across shared infrastructure, app architecture, reliability, and scaling • Have experience building internal apps,

About the Team The Future of Computing Research team is an Applied Research team within the Consumer Devices group focused on developing new methods and models as we advance forward in our mission of building AGI that benefits all of humanity. As a Software Engineer 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. About the Role We are looking for a Software Engineer to join our team to build tools and services that enable AI research, evaluation, and data generation workflows. The best work in this role will start with an ambiguous design question and turn it into working research systems. You will work closely with researchers, designers, and engineers to build the evaluation systems, synthetic data generation pipelines, review tools, and supporting platform services. The goal is to make these workflows easier to create, run, and trust without requiring bespoke engineering support for each new design concept. You will help ensure that research artifacts have a clear lifecycle, runs are reproducible and observable, and results provide useful evidence for product and model-training decisions while the underlying systems remain reliable and reusable. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: Build web applications, APIs, data models, and backend services for AI research workflows. Build tools to author and manage evaluation tasks, rubrics, graders, suites, and rollout configurations, including workflows for publishing, versioning, auditing, and sharing research artifacts. Automate evaluation runs and generate useful reports for design, research, and engineering teams. Support synthetic data generation workflows for multimodal and conversational research, including tools that comb

About the Team The OpenAI 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. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role As a Software Engineer, Distributed Data Systems, you will design, build, and operate some of the largest distributed data systems in the world. You will be responsible for the end-to-end stack to deliver and consume top-quality data for robotics training at exabyte-scale. You’ll manage distributed data pipelines, collaborate closely with researchers to translate requirements into robust systems, and harden pipelines that serve as the backbone for OpenAI’s rapid iteration cycles. We’re looking for engineers who are detail-oriented, have strong experience with distributed systems, and excel at building reliable, large-scale systems in high-stakes environments. 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: Design, build, and maintain data infrastructure such as exabyte-scale distributed data processing, data selection, automated labeling, and training data loaders. Ensure our data platform can scale by orders of magnitude while remaining reliable and efficient. Partner with researchers to deeply understand requirements and translate them into production-ready systems. Harden, optimize, and maintain critical data infrastructure systems that power multimodal training and evaluation. Deliver the best possible data for training robotics models. You might thrive in this role if you: Have strong experience with distributed systems and large-scale infrastructure with a strong interest in data. Are detail-oriented a

About the Team OpenAI is building the infrastructure foundation for the next generation of AI. The Data Center Engineering team defines the strategy, reference architectures, technical requirements, and delivery standards for the large-scale data centers that support OpenAI research, products, and infrastructure partners. As a Data Center Infrastructure Electrical Engineer, you will help define, validate, and scale the electrical power systems that support high-density AI compute. You will translate evolving compute requirements into practical facility and rack-power architectures, evaluate new technologies and vendor solutions, and drive technical decisions across design, manufacturing validation, construction, commissioning, deployment, and operations. This role is best suited for a senior hands-on engineer with deep experience in mission-critical power systems, strong judgment under ambiguity, and the ability to connect facility infrastructure, hardware requirements, controls, telemetry, reliability, and operations. About the Role We are seeking a senior electrical infrastructure engineer to lead the development of reliable, scalable, and efficient power architectures for high-density, liquid-cooled AI data centers. The ideal candidate has strong practical experience with critical electrical systems at data centers or comparable industrial scale, including medium-voltage and low-voltage distribution, utility interfaces, backup power, UPS and battery systems, rack power delivery, grounding, protection, controls, and monitoring systems. You should be comfortable moving between long-range architecture, detailed engineering review, lab validation, vendor qualification, field deployment, and operational troubleshooting. Key Responsibilities Design and optimize electrical topologies and equipment strategies that reduce cost, accelerate schedules, improve efficiency, increase scalability, and maintain high reliability and maintainability. Review and develop basis-of-des

About the Team: The Database Systems team specializes in high-performance distributed databases. Our team built Rockset, the real-time search, analytics, and vector database that powers all vector search and retrieval augmented generation (RAG) at OpenAI. In addition to retrieval, as an online database, Rockset powers core functionality across all of OpenAI's product lines and many critical internal use cases. About the Role : We are looking for engineers passionate about distributed systems, close-to-the-metal performance optimization (our core engine is written in C++), and building scalable database infrastructure from the ground up. As an engineer on the Database Systems team, you'll contribute to the core database engine, driving improvements across ingestion, query execution, indexing, and storage. You'll partner with teams across OpenAI to unlock new product capabilities and help scale online database reliability and throughput as usage grows by orders of magnitude. In this role you will: Design, build, and operate high-performance distributed systems Identify and resolve performance bottlenecks to scale infrastructure to the next order of magnitude Define long-term technical direction and guide system evolution Collaborate with product, engineering, and research teams to deliver scalable and reliable infrastructure Dig deep into complex production issues across the stack Contribute to incident response, postmortems, and best practices for system reliability You might thrive in this role if you: Have significant experience building, scaling, and optimizing distributed systems at scale Are curious about database internals, storage engines, or low-latency query systems Enjoy debugging challenging performance issues in complex, high-throughput systems Have experience operating production clusters at scale (e.g., Kubernetes or other orchestration systems) Think rigorously about scalability, correctness, and reliability Thrive in fast-paced environments with high

About the Team: OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. Our Stargate program develops and deploys massive, state-of-the-art data center campuses in partnership with industry leaders today—and through future OpenAI infrastructure projects tomorrow. We design for scale, speed, and reliability, and we need experienced technicians who can translate network blueprints into physical reality. About the Role: We are seeking a Senior Data Center Networking Technician who thrives in fast-moving build environments and is eager to roll up their sleeves during active datacenter deployments. Your first assignment will focus on the physical bring-up of network infrastructure at a large partner-operated campus, collaborating with partner teams and their delivery vendors to achieve agreed performance and reliability targets. As that campus reaches steady state, you will transition to lead network deployment for future OpenAI data center projects, defining standards and guiding implementation across multiple locations. Candidates must be able to sit onsite in Abilene, Texas 5 days per week Key Responsibilities Serve as OpenAI’s technical lead technician during the current campus build, partnering with internal engineers and external contractors on design reviews, installation plans, and acceptance criteria. Spend significant time on the data-center floor performing inspections, assisting with cable routing/termination when needed, conducting fiber testing (OTDR, power levels, continuity), and resolving installation challenges in real time. Troubleshoot and optimize cabling routes, patching, and equipment turn-up to ensure clean, reliable handoff to network operations. Contribute to design discussions and peer reviews for structured cabling and physical network layouts, providing practical field feedback to engineering teams. Develop repeatable engineering standards, as-built do

About the Team The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. You’ll join the team responsible for running the core infrastructure that supports products like ChatGPT and the API. The systems we support include our kubernetes clusters, infrastructure deployment, our networking stack, cloud abstractions, and more. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role The cloud infrastructure team builds and maintains infrastructure abstractions allowing OpenAI to ship products quickly and scalably. This role is based in San Francisco, CA. In this role, you will: Design and build the development and production platforms that power our products, enabling reliability and security at scale Ensure our infrastructure can scale to the next order of magnitude Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed. You might thrive in this role if you: Have 5+ years building core infrastructure Have experience operating orchestration systems such as Kubernetes at scale Have experience building abstractions over cloud platforms Take pride in building and operating scalable, reliable, secure systems Are comfortable with ambiguity and rapid change This role is exclusively based in our San Francisco HQ. We offer relocation assistance to new employees. 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 depl