System Engineer Cloudflare Hyperdrive Salary India in United States

About the Team The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to help build the core monetization and ads systems at OpenAI. This is a foundational role responsible for designing and implementing the infrastructure, APIs, and user-facing experiences that will power OpenAI’s next-generation monetization products—including ads. You’ll work across the full technical stack to architect, build, and ship 0→1 systems that are robust, safe, and scalable. You will collaborate deeply with Product, Design, and Research to define the future of monetized AI experiences and ensure these systems meet OpenAI’s highest standards for safety, privacy, and policy alignment. This role is exclusively based across our San Francisco and Seattle sites. We offer relocation assistance to new employees. In this role, you will: Design, build, and scale the core infrastructure behind OpenAI’s monetization and ads products Develop advertiser-facing APIs and tools that enable the cre

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 OpenAI Robotics depends on high-quality real-world robot data from a large, live operational environment. That environment has many deployed workcells, changing configurations, and little tolerance for downtime. We are seeking a Field Engineer to help keep that environment running well. You will own the day-to-day technical health of robotic workcells used in ongoing data acquisition operations, diagnose and resolve failures across hardware and software, and build the practical tools, documentation, and support workflows that make operators and technicians more effective. The work is close to the floor, close to the failure modes, and close to the research impact. This role sits at the intersection of software, robotics hardware, and live operations. The best people in it are practical, technically sharp, calm under pressure, and motivated by making real systems work reliably at scale. This role will be based in San Francisco, CA 5 days per week and offer relocation assistance to new employees. In this role, you will: Serve as an engineering owner for keeping a fleet of robotic workcells online in daily operation. Diagnose, fix, mitigate, or escalate issues spanning mechanics, electronics, controls, software interfaces, logs, and configuration. Partner closely with technicians, operators, and engineering teams to improve scalable fleet support processes. Build or spec lightweight hardware and software tools that improve monitoring, diagnostics, recovery, and handoffs. Create documentation, SOPs, and diagnostic playbooks that turn en

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 Statsig team within OpenAI owns the experimentation, rollout, dynamic configuration, and analytics infrastructure that sits on the launch path for OpenAI products. Our systems help teams ship safely, evaluate product and model changes in production, and make high-confidence decisions from real-world usage. Statsig began as an independent company built around experimentation, feature management, and product analytics at scale. After Statsig joined OpenAI, the team began the next chapter: bringing that platform expertise and infrastructure into OpenAI as the experimentation and rollout foundation for every product we ship. This is infrastructure with a very direct product consequence. Teams working on ChatGPT, Codex, model measurement, consumer experiences including ads, business subscriptions, developer products, and shared platform systems depend on Statsig to evaluate configurations, move traffic safely, ingest experiment data, serve analytics, and roll changes forward or back when production reality demands it. We are at a critical point in the platform journey. Adoption is accelerating quickly across OpenAI, and the systems that were already important are becoming load-bearing for how the company launches. The infrastructure needs to stay fast under sharply increasing evaluation volume, reliable when more services depend on it, observable enough to debug quickly, and efficient enough to support OpenAI-wide scale. Recent SDK and server-side infrastructure work has already produced measurable wins in latency, reliability, memory usage, and compute efficiency across important services. The next phase is to make those gains systematic: a platform that can absorb rapidly growing product velocity while preserving low latency, data quality, operational safety, and developer trust. Based out of OpenAI's Bellevue office, we are a close-knit team that values in-person collaboration, technical depth, operational ownership, and building infrastructure that

About the Team We’re hiring software engineers to make OpenAI’s Model Performance teams more productive. These teams work on the systems, tooling, and infrastructure that help improve model performance across OpenAI’s training and inference workloads at frontier scale. About the Role We’re looking for an autonomous, high-ownership developer productivity engineer who cares deeply about helping other engineers move faster, safer, and with more confidence. This role will sit within OpenAI’s Model Performance organization, contributing to developer infrastructure, CI systems, testing workflows, tooling, and broader performance infrastructure efforts. There is also a strong opportunity to contribute to the Triton project and help improve the systems that support performance-critical engineering work across OpenAI. In this role you will: Improve development workflows for engineers working on model performance infrastructure Design and improve CI/CD, release, validation, and testing pipelines Build and maintain tools that improve reliability, iteration speed, and engineering confidence Partner closely with engineers to identify friction in testing, debugging, deployment, and development workflows Contribute to infrastructure efforts that support performance-critical training and inference systems Help improve developer experience across Python-heavy codebases and performance-oriented infrastructure Work in a high-context, ambiguous environment where ownership and good judgment matter You might thrive in this role if: You are motivated by enabling the people around you and helping engineers do their best work You have strong experience with CI/CD, developer infrastructure, testing systems, tooling, or build/release workflows You are highly collaborative, empathetic, and comfortable partnering deeply with technical teams You are strong in Python and enjoy building reliable, scalable developer tools and infrastructure You have experience improving large-scale engineering work

About the Team Our team analyzes inference stack performance across the application, model, and fleet layers to identify bottlenecks and drive faster, cheaper inference. We combine systems profiling, benchmarking, and analysis to understand where time and cost are spent, then turn that understanding into performance optimizations and models that project performance and capacity needs for future launches. About the Role In this role, you will model inference performance across application, model, and fleet layers with higher fidelity. You will build cost-to-serve estimates from microbenchmarks and create tools that help cross-functional teams reason about latency, capacity, utilization, and cost tradeoffs. In this role, you will Build and refine performance models that translate microbenchmark results into cost-to-serve estimates. Analyze inference workloads end to end across applications, models, and fleet infrastructure. Enhance tooling to identify bottlenecks across layers for latency and throughput. Partner with other teams to turn performance insights into concrete improvements and project how future changes affect inference. You might thrive in this role if you: Enjoy reasoning from first principles about distributed systems, model inference, and hardware efficiency. Are comfortable working across abstraction layers, from application behavior to kernels, accelerators, networking, and fleet scheduling. Have deep expertise with performance profiling, benchmarking, analysis, and optimization. Enjoy collaborating with engineering and research teams to improve real production 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 extremely powerful tool that must be created with safety and human needs at its core, and to achieve o

About the Team The Statsig team within OpenAI builds the experimentation, feature rollout, dynamic configuration, and analytics systems that help OpenAI ship products with speed, safety, and evidence. Our work sits on the critical path for how product, engineering, research, and go-to-market teams learn from real-world usage and make high-confidence decisions. Statsig began as an independent company focused on helping builders move faster through trustworthy experimentation and feature management. After Statsig joined OpenAI, the team began the next chapter: bringing that deep product expertise, customer intuition, and mature platform infrastructure into OpenAI as the experimentation and rollout platform for every product we ship. Today, we support teams across ChatGPT, Codex, model measurement, consumer experiences including ads, business subscriptions, developer products, and the shared infrastructure that connects them. These teams rely on Statsig to safely introduce new capabilities, compare product and model behavior, measure impact, and roll changes forward or back with confidence. We are at a defining moment in the platform journey. OpenAI has the data, product surface area, and pace of innovation to learn faster than almost any organization in the world, but that potential only becomes real if teams can experiment responsibly, measure clearly, and roll out changes safely. Adoption of the platform is accelerating rapidly across the company, and recent SDK and server-side infrastructure work has already produced measurable wins in latency, reliability, memory usage, and compute efficiency for important services. Based out of OpenAI’s Bellevue office, we are a close-knit team that values in-person collaboration, urgency, craft, and impact. We build for other builders, and the best version of this team is one where every OpenAI product team can move faster because the experimentation and rollout layer is dependable, fast, and easy to use. About the Role We are l

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Senior Software Engineer — Cortex Training The Snowflake ML Platform team's mission is to let customers run their most demanding ML/AI workloads inside Snowflake. Cortex Training is our LLM post-training platform: it turns scarce, expensive GPU capacity into a simple, composable service, so customers can adapt open-weight foundation models to their own business problems while we handle the hard distributed-systems parts, including scheduling, orchestration, multi-node training and inference, fault tolerance, and throughput. The platform already runs post-training at scale. Under the hood, it decouples GPU computation from the training loop and exposes it as primitive APIs that compose into everything from SFT to full RL workflows. You'll work alongside a team that ships fast & sweats reliability and the researchers behind DeepSpeed. We're looking for an engineer who thrives in the ML infrastructure layer and brings a solid understanding of LLMs and post-training to help us scale and grow it. YOU WILL: Design and build across the full stack — from the public training APIs and SDK through the control plane to the GPU data plane. Scale the distributed systems that make GPU compute serverless — multi-tenant scheduling, placement, and capacity-aware routing across regional G

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. As a Lead Migrations Forward Deployed Engineer (Migration FDE), you will lead scoping, architecture and direction as the FDE team embeds with customers to lead the modernization of their data and application ecosystem using the Snowflake AI Data Cloud. You will partner closely with clients to understand their business challenges to design, build, and implement cutting-edge data solutions on Snowflake. Your role is crucial in enabling customers to harness the full potential of their data, driving insights, and powering AI initiatives. You'll act as a trusted technical advisor, ensuring customers achieve significant business value and success with Snowflake. WHAT YOU WILL BE RESPONSIBLE FOR: Migration Project Execution : You will work with multiple FDE teams that each focus on a specific customer. You’ll set architecture and direction for the team as it works to design, build, and deploy robust software systems, tooling, and automation required to support customer solutions on Snowflake. Software Development: All Migration FDE members, leads and otherwise, contribute to our product. We build prototypes, contribute to feature development, fix problems that we find. Doing so helps drive impact on the roadmap and improves individual depth in the product itself. Client Collaborat

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. As a Senior Forward Deployed Engineer (FDE), you will be embedded with customers to lead the modernization of their data and application ecosystem using the Snowflake AI Data Cloud. You will especially focus on modernizing their Spark and Data Engineering focused workloads. You will partner closely with clients to understand their business challenges and design, build, and implement cutting-edge data solutions on Snowflake. Your role is crucial in enabling customers to harness the full potential of their data, driving insights, and powering AI initiatives. You'll act as a trusted technical advisor, ensuring customers achieve significant business value and success with Snowflake. WHAT YOU WILL BE RESPONSIBLE FOR: Software Development : Design, build, and deploy robust software systems, tooling, and automation required to support customer solutions on Snowflake. Create comprehensive documentation for developed solutions, technical configurations, and best practices. Data Engineering & Platform Implementation : Design and implement scalable data pipelines and modern data architectures on Snowflake. Ensure data quality, integrity, and efficient processing within the customer's modern data environment. Performance Optimization & Best Practices : Analyze and optimize data

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About the team The Apps & Experiences Platform team powers the systems and services behind all of our user-facing applications, including Snowsight, Snowflake Intelligence, and new mobile experiences. Our mission is to build innovative backend services, developer tooling, platform infrastructure, and AI-powered capabilities that enable exceptional product experiences at scale. As part of our team, you’ll work across feature development, platform engineering, infrastructure, and internal tooling to support both end users and developers. We care deeply about building systems that are reliable, scalable, maintainable, and performant. Snowflake is a high-growth AI Data Cloud company, and we’re looking for exceptional engineers to help us scale the next generation of our platform. A key part of this is our work on our internal AI developer agent, which is designed to democratize end-to-end app development across all engineering teams by translating product specs and designs into fully functional, production-ready features. AS A SENIOR SOFTWARE ENGINEER FOR THE APPS & EXPERIENCES PLATFORM TEAM, YOU WILL: Design, build, and operate scalable backend services and platform infrastructure that power Snowflake’s user-facing applications. Contribute across the full development l

As TaylorMade continues to grow, the number and complexity of integrations are increasing. TaylorMade maintains a substantial number of data interfaces across multiple time zones, operating 24/7, many involving multi-step processes and connecting several major global applications. This ecosystem requires continuous monitoring, support, and enhancement. The Senior Software Engineer, Integration is responsible for the ongoing improvement and evolution of TaylorMade’s enterprise application integration (EAI) environment, including supporting processes, procedures, and technologies. The successful candidate will demonstrate expertise in delivering modern, high-performing, and secure business software systems using cutting-edge technologies and tools, including middleware, iPaaS, and cloud-based databases. This position is responsible for designing and building best-in-class application integration architectures and interfaces, leveraging both real-time and batch integration patterns. Essential Functions and Key Responsibilities: Participate in all aspects of high-level planning, design, development, and deployment of data integrations. Lead middleware and application interface activities, utilizing a strong EAI background to develop solutions. Design and architect ETL solutions for on-premise to on-premise, on-premise to cloud, and cloud-to-cloud scenarios. Participate in technical discussions and provide guidance and expertise for Informatica and related middleware and data architecture technologies. Ensure all interfaces and middleware components perform as expected and are proactively monitored and managed for availability and capacity. Employ strong problem-solving skills and a proactive attitude, taking full ownership of assign

Chief Engineer - Patriot Advanced Capability (PAC-3) Company: The Boeing Company Boeing Defense, Space & Security (BDS) is searching for an inspiring and visionary Chief Engineer to lead groundbreaking engineering transformation for the PAC-3 Acceleration Efforts in Huntsville, AL . This pivotal role offers a unique opportunity to be at the forefront of accelerating production rates by driving innovative design for manufacturability and testability, optimizing production systems, and pioneering advanced engineering solutions that empower high-rate manufacturing success. As production demands soar, you will be the catalyst transforming engineering processes and production capabilities—ensuring we not only meet ambitious acceleration targets but also uphold Boeing’s renowned standards of quality and technical excellence. The Chief Engineer will serve as a strategic technical leader, spearheading engineering changes essential to unlocking higher production rates. You will collaborate seamlessly with engineering, manufacturing, quality, supply chain, and production teams to enhance product designs and processes geared toward efficiency, scalability, and continuous improvement. Position Responsibilities: Lead and champion engineering transformation initiatives to significantly accelerate PAC-3 production rates Drive and embed design for manufacturability (DFM), design for testability (DFT), and design for assembly (DFA) practices that enable smooth, high-rate production Partner closely with manufacturing and production teams to innovate and implement enhancements in production systems, tooling,

Manufacturing Engineer (Associate or Experienced) Company: The Boeing Company Boeing Defense, Space & Security (BDS) Laser and Electro-Optical Systems (LEOS) site is seeking an Experienced Manufacturing Engineer for our advanced development and production manufacturing team located in Albuquerque, NM. The Boeing Laser and Electro-Optical systems (LEOS) group works to develop and implement next-generation technologies and products serving a variety of commercial and military customers. Our team focuses on rapid prototyping and precision production of advanced laser and electro-optical systems that satisfy challenging product performance requirements built in accordance with aerospace (AS9100) quality standards. Position Responsibilities: Design, develop and optimize manufacturing processes and tooling approaches for complex electro-optical aerospace parts and assemblies Collaborate with design engineers to ensure manufacturability and cost-effective production Review engineering drawings and provide comments to responsible engineer Participate in Integrated Product Teams (IPTs) to integrate technical solutions across multiple disciplines Participate in supplier selection and evaluation to ensure adherence to quality and delivery standards Write content for work instructions, travelers, and standard shop procedures Utilize electronic work instruction, material control and non-conformance management systems as needed to support production Ensure compliance with aerospace industry quality standards (e.g., AS9100, J-STD) Ensure the manufacturing work instructions and special processes follow safety and environmental regulations Assist in shop layout and

JLL empowers you to shape a brighter way . Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward. Operating Engineer, Data Centers What this job involves - The Operating Engineer assists with critical environment (CE) engineering operations monitoring and performing preventive maintenance and continuous operation of all data center systems. The position will have a strong focus on data center mechanicals, electrical equipment troubleshooting and repairing CE facility equipment, and learning the core functions of an operating engineer. Your day-to-day tasks will include - Conduct routine inspections and preventive maintenance of equipment and systems (e.g., cooling systems, electrical systems, generators, fire suppression, UPS systems) to ensure the smooth operation of the data center. Monitor building management systems and respond to alarms and alerts promptly. Assist in diagnosing and resolving operational issues in the data center, including electrical, mechanical, and network-related problems. Collaborate with senior engineers to troubleshoot complex technical issues and implement appropriate solutions. Assist with the installation, configuration, and testing of new equipment. Assist in coordinating equipment upgrades and modifications.</l