About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.
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Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: Providing world-class customer service for our community of guests and hosts is a critical mission at Airbnb. The Ambassador Routing & Channels (ARC) team sits within Airbnb Community Support and is responsible for powering intelligent, differentiated service experiences, ensuring every support request, across any channel, is addressed by the right expert at the right time. Our work directly drives faster resolutions, higher quality interactions, and exceptional customer satisfaction at scale. The Difference You Will Make: As a Staff GenAI Backend Engineer on the ARC team, you will drive meaningful impact across our core routing and differentiated service programs: Lead engineering delivery on strategic programs that enable intelligent agent matching, personalized support experiences for high-value customers, and next-generation routing and communication channel capabilities. Own and evolve core routing infrastructure, including decision engines, workflow orchestration, and routing rule management. Ensuring high availability, correctness, and scalability across millions of daily support interactions. Drive consolidation of fragmented routing logic spread across multiple platforms and channels into a centralized, auditable, and maintainable system. Collaborate cross-functionally with Product, Operations, Data Science, and partner engineering teams to align on priorities and deliver outcomes that improve the customer support experience. Contribute to technical quality through design reviews, code reviews, and pragmatic architectural decision-making. Play a critical role in buildin
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. We are hiring for Machine Learning Engineering as TL level. Your Location: This position is CHINA BASED. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. Your recruiter will inform you what cities you are able to work from depending on your personal legal working identity and Airbnb internal policies. The Community You Will Join: Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb. The Community Support Products (CSP) Machine Learning team is the core team responsible for driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting the Generative AI technologies to enable an intelligent, scalable and exceptional service experience. The team develops and enhances various AI models, ML services and tools including LLM fine-tuning and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb. The richness of Airbnb's data, the complexity of its marketplace and the variety innate in our product mean that we need to operate at the state of the art of AI practice. We are committed to investing in long term innovation to solve the complex problems we face, and to do that we need the very best experts in ML and AI to join us. The Difference You Will Make: We believe our current customer experiences in these domains are
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: The Growth Platform team’s vision is to drive long term sustainable growth for the Airbnb community. Our mission is to build a best-in-class agentic system, and capabilities to support the growth of all Airbnb products, current and future. We achieve this by delivering highly personalized and relevant content and product experiences to the Airbnb community, both on and off of the Airbnb platform. The north star is full autonomy — where AI identifies opportunities, creates campaigns, personalizes experiences, and optimizes outcomes with minimal human intervention. We are progressing along a deliberate maturity curve: AI assisted → agentic → autonomous, with human-in-the-loop controls at every stage to ensure brand safety, quality, and compliance. The Growth Platform deeply integrates with the Airbnb product, understanding the customer journey and enabling differentiated customer engagement experiences to drive product growth. The platform also powers digital marketing channels including landing pages, email, push, SMS, and digital advertising, as well as the machine learning/AI and data platforms that feed into the management and optimization of these channels. The Difference You Will Make: As a machine learning engineer or scientist, your expertise will be pivotal in developing AI-powered solutions to shape the future of the Airbnb agentic growth platform with cutting-edge AI techniques. You will drive and guide the rest of the engineers to brainstorm, design and develop AI products and features from inception to production. We're seeking a Senior Staff Engineer who thri
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb. The Community Support Products (CSP) Machine Learning team is the core team responsible for driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting the Generative AI technologies to enable an intelligent, scalable and exceptional service experience. The team develops and enhances various AI models, ML services and tools including LLM fine-tuning and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb. The richness of Airbnb's data, the complexity of its marketplace and the variety innate in our product mean that we need to operate at the state of the art of AI practice. We are committed to investing in long term innovation to solve the complex problems we face, and to do that we need the very best experts in ML and AI to join us. The Difference You Will Make: We believe our current customer experiences in these domains are only scratching the surface of the innovations that are possible, and that science is at the heart of delivering a step-function change for our Guest and and Host on Airbnb. You will build and leverage cutting edge AI technologies to transform Airbnb’s customer service by delivering personalized, easy-to-use and proactive customer service experience. Many of the initiatives you’l
Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Join the Pipeline Engineering team at Everpure™ as a Software Engineer to build, own, and operationally scale the microservices and Temporal workflows driving continuous integration for FlashArray, FlashBlade, and Hyperscale. In this developer-first role based in Bangalore, you will design durable production services and agentic AI tools that directly reduce time-to-signal, optimize compute utilization, and absorb operational toil across our global engineering workforce. WHAT YOU'LL DO Architect Deterministic CI Workflows: Design and deploy production microservices and durable Temporal workflows that make pipeline execution resilient, resumable, and fully debuggable for enterprise storage platforms. Optimize Compute & Testbed Utilization: Extend in-house scheduling logic and placement algorithms across bare-metal hardware and VM fleets to minimize queue times and maximize infrastructure efficiency. Build Operational AI Agents: Engineer RAG pipelines and agentic workflows over failure logs, vector stores, and test metadata to automate root-cause analysis, flake classification, and developer triage. Drive Platform Observability & Ownership: Establish key platform metrics—including time-to-signal and pass/flake rates—while operating your services end-to-end to ensure long-term stability and eliminate recurring failure modes. Collaborate Across Product Teams: Partner with platform and product engineering group
About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: At Modal, we sell cloud services atop which our customers run their critical production systems. As a rapidly growing new cloud infrastructure company, we seek to improve our reliability dramatically while scaling the size of our platform, customer base, and our team. This role is for people who are deep systems thinkers, love stacking nines, and thrive from making others move faster at scale. Responsibilities include: Identifying architectural changes to improve reliability and performance. Fostering a culture of reliability across Modal’s engineering organization. Defining and implementing operational processes such as deployments, upgrades, etc. Operating systems like Kubernetes, Postgres, Redis, etc. Participating in on-call rotations, and responding to production incidents. Requirements: 5+ years of experience writing high-quality production code. 2+ years of
We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Security Engineering is the engineering function inside the Plaid security org that focuses on developing the industry-leading security systems and infrastructure. Security Engineering owns most of Plaid’s security-related infrastructure: secure data storage, key management systems, internal identity platform, internal authentication systems, internal permission management, and internal authorization service. We develop solutions across data encryption, key management, access control, and data loss prevention to protect sensitive consumer data. We believe in the Zero Trust security model and are always looking for ways to improve our authentication and access control platforms. About the role: You will develop security capabilities to secure Plaid infrastructure and sensitive data access. You will lead the team’s strategic planning in collaboration with the manager and other senior engineers. You will own, maintain, and build Plaid’s security infrastructure and services like IAM Gateway, Key Management System and Network Firewall. You will consult with product engineers to ensure Plaid services meet security standards. You will help educate and support other engineering teams to improve security in
About the Team The Consumer Devices team at OpenAI builds end-to-end hardware and software systems that bring AI into the physical world. We work at the intersection of custom silicon, embedded systems, operating systems, cloud services, mechanical engineering, electrical engineering, and product design to deliver reliable, production-ready devices at scale. Within Consumer Devices, Hardware Engineering eXperience, or HEX, is a new bootstrapped team building the environments, applications, compute, product-data systems, and workflows that let hardware engineers do their work without needing to troubleshoot the machinery underneath. HEX owns virtual engineering environments, HPC/GPU compute, storage, networking, licensing, MCAD/ECAD/CAE applications, PLM, product data, automation, validation, and support as one connected system. About the Role As a Staff PLM & Engineering Applications Engineer, you will be one of the first technical builders of HEX and the primary counterpart to the HEX lead. You will own the engineering-application and product-data side of the hardware engineering experience, with an initial focus on NX, Teamcenter, licensing, parts import, integrations, packaging, validation, and user workflows. This is not a traditional Teamcenter administration role and not a Corporate IT application-support role. You will take complex, fragile workflows and turn them into reliable engineering systems. This role is highly hands-on and systems-oriented. You will not inherit a mature environment and support queue. You will help build a fresh one, replacing manual setup guides, tribal knowledge, repeated support issues, and team handoffs with tested automation and reliable workflows. In This Role, You Will Own the technical architecture, deployment, configuration, integration, validation, and long-term operation of NX and Teamcenter. Build reliable workflows for parts import, product-data migration, metadata quality, BOMs, revisions, lifecycle states, and releas
Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us—that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale—from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role Nuro's autonomous vehicle platform has to work - not just in the easy cases, but in the hard ones. The ones we design for, simulate at scale, and deliberately break to understand. We're looking for a Senior/Staff Systems Engineering TPM who owns the technical substance of how we validate autonomy: what we test, why we test it, and whether our coverage actually means something. This is not a planning or scheduling role. You'll work embedded with Autonomy, Simulation, and Systems Engineering teams to drive the technical rigor behind our validation program — defining scene sets, structuring fault injection campaigns, and ensuring our simulation coverage is meaningful, traceable, and systematically growing. The program infrastructure is owned elsewhere; your job is to make sure what's inside it is technically sound. About the Work Scenario & Coverage Strategy Understanding the taxonomy of challenging scene sets used for auto
As a TPM for SRE, you will partner with SRE leaders and engineers to scale the platform that underpins all of MongoDB’s cloud products. You will drive program execution, strengthen production reliability practices, and coordinate cross-functional efforts across US and EMEA teams. Success in this role means smoother launches, clearer roadmaps, stronger reliability metrics and an SRE organization that's better-equipped to deliver predictability at scale. This role can be based out of our Dublin or Cork office or remotely in Ireland. What You'll Do Drive Program Planning & Execution – Define program scope, milestones, and success criteria with SRE engineers and leaders. Manage dependencies across platform teams, keep work clearly tracked in Jira, and deliver on time Strengthen Production Reliability – Lead change management and launch readiness programs. Partner with SREs and product teams to define and operationalize SLOs/SLIs, and use incident data, metrics, and capacity signals to drive prioritization and continuous improvement Lead Cross-Functional Coordination – Align SRE with Security, Compliance, Cloud platform, and other engineering teams. Coordinate cross-team incident response, ensure clear follow-through, and build trust as the go-to driver of complex, multi-team efforts Build Scalable Systems & Processes – Design lightweight frameworks and communication patterns that help SRE deliver reliably at scale. Work yourself out of the "hero" role by leaving teams better-equipped to execute independently Requirements 8+ years in technical program management, engineering management, or a comparable technical role partnering with software engineering teams Proven track record leading large-scale, cross-team platform initiatives through ambiguity and change Strong knowledge of production change management, software development lifecycle, and reliability metrics (SLOs, SLIs) Skilled at shaping roadmaps and managing dependencies Able to query and interpret
As a TPM for SRE, you will partner with SRE leaders and engineers to scale the platform that underpins all of MongoDB’s cloud products. You will drive program execution, strengthen production reliability practices, and coordinate cross-functional efforts across US and EMEA teams. Success in this role means smoother launches, clearer roadmaps, stronger reliability metrics and an SRE organization that's better-equipped to deliver predictability at scale. This role can be based remotely on the East Coast What You'll Do Drive Program Planning & Execution – Define program scope, milestones, and success criteria with SRE engineers and leaders. Manage dependencies across platform teams, keep work clearly tracked in Jira, and deliver on time Strengthen Production Reliability – Lead change management and launch readiness programs. Partner with SREs and product teams to define and operationalize SLOs/SLIs, and use incident data, metrics, and capacity signals to drive prioritization and continuous improvement Lead Cross-Functional Coordination – Align SRE with Security, Compliance, Cloud platform, and other engineering teams. Coordinate cross-team incident response, ensure clear follow-through, and build trust as the go-to driver of complex, multi-team efforts Build Scalable Systems & Processes – Design lightweight frameworks and communication patterns that help SRE deliver reliably at scale. Work yourself out of the "hero" role by leaving teams better-equipped to execute independently Requirements 8+ years in technical program management, engineering management, or a comparable technical role partnering with software engineering teams Proven track record leading large-scale, cross-team platform initiatives through ambiguity and change Strong knowledge of production change management, software development lifecycle, and reliability metrics (SLOs, SLIs) Skilled at shaping roadmaps and managing dependencies Able to query and interpret metrics, logs, or other data s
We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Plaid's Infrastructure team builds the platforms and tooling that help engineering teams develop, deploy, and operate production systems safely. Release Engineering owns the path from merge to production, including Plaid's zero-touch deployment system, progressive rollouts, metric-gated analysis, and automatic rollback. Our goal is to make safe shipping the default for every product team. As a Staff Site Reliability Engineer on Release Engineering, you'll define and scale Plaid's reliability practices across product engineering. You'll architect our SLO and error-budget programs, drive the adoption of progressive delivery, and ensure new products are production-ready. By partnering across product and platform teams, you'll translate complex production needs into intuitive, self-service tooling. This is a hands-on technical leadership role where you'll shape the future of our deployment systems—ensuring they remain fast and safe even as AI-assisted development increases code velocity. What excites you Lead the expansion of reliability standards across product engineering, converting foundational infrastructure into lasting operational habits and tooling. Architect and manage the SLO and error-budget
GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Staff Engineer, you'll be the technical anchor for GitLab's Nonlinear Productivity team in the US: the person who decides what "proven" means before something ships, and who helps shape what the team builds next, not just how to build it. It's a from-scratch, generalist team with no dedicated product manager — that ownership starts on day one. Some examples of the problems this team takes on: Cutting the time it takes to complete a good code review — one that still keeps a human in the loop — by half, using agentic solutions. Turning a manual, error-prone release step into an agentic workflow that ca
About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest is seeking a Staff Software Engineer, Capacity Engineering. The team is responsible for efficiently managing one of the largest-scale cloud-native infrastructures in the world. This role is highly impactful, as efficiency is an ongoing strategic priority for Pinterest. The role has direct visibility across Pinterest Engineering and with Engineering and company leadership. The team is looking for a candidate with a strong background in implementing performance and efficiency projects on large scale distributed systems. In this individual-contributor role you will own and drive performance and efficiency for a core area of Capacity Engineering, partnering with the company-wide efficiency lead and collaborating with performance and efficiency leaders across the organization. What you’ll do: Drive efficiency in large-scale shared environme
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