Infrastructure Team Manager in United States

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: We are looking for an Advanced Analytics Lead to help Airbnb enable travel for our millions of guests and hosts on our platform. This role will sit under the Advanced Analytics family and support Product and Business leaders within our CS organization. The Difference You Will Make: Data thought partner to product and business leaders across teams through providing insights, recommendations, and enabling data informed decisions Drive day to day analytics and create scalable data tools Identify pain points in customer support operations and work with product leadership to improve experiences for our guest, host and agent community In addition, you will leverage Airbnb’s rich and unique data, state-of-art machine learning infrastructure, and other central data science tools to build and grow the measurement capacity within the organization. You will also be deeply involved in the technical details of the various systems we build, and will have the opportunity to collaborate with a strong team of engineers, product managers, designers and operations agents to achieve shared, cross-functional goals to help keep Airbnb’s community safe and trusted. You are passionate about solving complex problems within the Community support domain with data & insights; adding a new perspective to existing solutions and making business decisions based on careful and thoughtful analysis You are highly proficient in building and analyzing analytical frameworks, statistical models and experimentation methods to establish and communicate causal relationships You are a story

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. 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 CS AI product team is 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, alignment and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb. What you will do: As a principal machine learning engineer, you will be responsible for fine-tuning state-of-the-art LLMs for diverse use cases while optimizing models for high-performance deployment on Airbnb’s ML Infrastructure. You will partner with product managers, software engineers, data scientists and operation teams to brainstorm, design and develop AI products such as AI Assistant, Autonomous agent, recommendation, travel planning, and many more products that make meaningful

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. We’re at the forefront of the data revolution, committed to building the world’s greatest data and applications platform. Snowflake started with a clear vision: develop a cloud data platform that is effective, affordable, and accessible to all data users. Data Cloud allows sharing live data in governed and secure ways so our customers can solve their business problems. Data Cloud allows sharing live data in governed and secure ways so our customers can solve their business problems. Come join our world-class team as a Software Engineer to build the backend services for data cloud to help our customers to share data internally within their company or outside with external organizations. We are investing in initiatives across multiple engineering areas that include: Data Engineering & Open Lakehouse, Database Engineering, Engineering Systems, Product Experiences, Apps & Collaboration,Platform Engineering, and Public Sector, Security and Governance AS A SOFTWARE ENGINEER, YOU WILL: Design and build features, and/or distributed platforms at scale. Drive impactful initiatives for the globally distributed infrastructure Collaborate with product managers, architects, other engineering teams, and business groups, to drive end-to-end solutions. Contribute to improving our en

This role will support the fleet infrastructure team at OpenAI. The fleet team focuses on running the world’s largest, most reliable, and frictionless GPU fleet to support OpenAI’s general purpose model training and deployment. Work on this team ranges from Maximizing GPUs doing useful work by building user-friendly scheduling and quota systems Running a reliable and low maintenance platform by building push-button automation for kubernetes cluster provisioning and upgrades Supporting research workflows with service frameworks and deployment systems Ensuring fast model startup times though high performance snapshot delivery across blob storage down to hardware caching Much more! About the Role As an engineer within Fleet infrastructure, you will design, write, deploy, and operate infrastructure systems for model deployment and training on one of the world’s largest GPU fleet. The scale is immense, the timelines are tight, and the organization is moving fast; this is an opportunity to shape a critical system in support of OpenAI's mission to advance AI capabilities responsibly. 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, implement and operate components of our compute fleet including job scheduling, cluster management, snapshot delivery, and CI/CD systems. Interface with researchers and product teams to understand workload requirements Collaborate with hardware, infrastructure, and business teams to provide a high utilization and high reliability service You might thrive in this role if you: Have experience with hyperscale compute systems Possess strong programming skills Have experience working in public clouds (especially Azure) Have experience working in Kubernetes Execution focused mentality paired with a rigorous focus on user requirements As a bonus, have an understanding of AI/ML workloads About OpenAI OpenAI is an AI resea

Cloud Infrastructure Administrator (Mid-Level, Senior or Lead) **Sign on Bonus Potential** Company: The Boeing Company The Boeing Company’s Specialized United States Infrastructure Operations organization is currently seeking a Cloud Infrastructure Administrator (Mid-Level, Senior or Lead) to join the team in Berkeley, MO; Seattle, WA; or Daytona Beach, FL . The Infrastructure team is seeking an experienced cloud infrastructure professional to help design, build, and sustain the foundational cloud environment supporting critical program needs. In this role, the selected candidate will help establish and operate secure, scalable, and resilient cloud infrastructure environments in Microsoft Azure to enable enterprise applications, software toolchains, and digital engineering workloads. As both an individual contributor and technical leader, this position will work across network, computer, storage, identity, security, and automation domains to deliver repeatable cloud infrastructure patterns and operational excellence. This role is focused on infrastructure operations, sustainment, automation, and reliability, rather than application software development. Position Responsibilities: Design, implement, and maintain Microsoft Azure-based infrastructure solutions including networking, compute, storage, identity integration, and supporting services Develop and maintain Infrastructure as Code (IaC) and configuration automation solutions using Terraform, Ansible, PowerShell, and Bash Implement cloud policies to enforce security, ensure regulatory compliance, and manage user access Build repeatable landing zones and cloud infrastructure patterns that support mul

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As an Infrastructure Software Engineer at Baseten, you'll build and maintain components of our ML inference platform that powers production AI applications. You'll contribute to the core infrastructure, enabling developers to deploy, scale, and monitor ML models with high performance. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Infrastructure team: Multi-cloud capacity management Inference on B200 GPUs Multi-node inference Fractional H100 GPUs for efficient model serving RESPONSIBILITIES Develop infrastructure components for our ML inference platform using Python and Go Implement and maintain Kubernetes deployments for model serving Contribute to our inference orchestration layer for model deployments Build and enhance monitoring systems for model performance metrics Implement efficient resource management solutions for ML workloads Support infrastructure automation to improve ML deployment workflows Work closely with team members to implement technical solutions Help balance performance optimization with system reliability Participate in technical discussions around infrastructure improvements Learn and apply infrastructure best practices REQUIREMENTS Bachelor's degree or higher in Computer Science or related field Proficient coding abilities in one or more popular programming or scripting languages; Go proficiency is a plus Working knowledge of Kubernetes and containeriza

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We’re looking for an early career Software Engineer to join our Infrastructure team to accelerate building and scaling our innovative systems that support our growing identity platform. In this role, you will build the next-generation infrastructure that underpins all systems at CLEAR. The ideal candidate for this role will approach challenges with an eye toward reliability, simplicity, and scalability. What You'll Do: Develop and maintain a streamlined process for engineers to effortlessly build and deploy scalable and reliable software-defined networking solutions on AWS. Enhance our compute platform (Kubernetes) with new functionalities and features, focusing on AWS networking services and concepts such as VPCs, Route Tables, Security Groups (SGs), ALBs/ELBs, and Route53, optimize service communication and management. Collaborate across engineering teams to advocate for and implement best practices in observability, utilizing tools like Splunk or Datadog to ensure robust network monitoring. Act as a product owner for our infrastructure, collecting feedback and requirements from engineering teams to address pain points and develop solutions, particularly in the realm of AWS networking and cloud-native design principles. What you're great at: 0-2 years of experience in infrastructure and platform development and AWS cloud services. Proficient in Python, with understanding of Kubernetes and container orchestration tools like EKS and ECS. Understand AWS networking services, including VPC design, SGs, NATGWs, ALBs/ELBs, Rout

About the Team The Storage Infrastructure team builds and operates the storage foundation behind OpenAI’s most demanding workloads. We work directly with research to design storage systems for rapidly evolving experiments, while also powering production at scale. We own the platform end to end: backend systems, user-facing services and APIs, and the control planes that manage how data is placed, moved, and retained over time. Our stack spans cloud and in-house object stores across very different workload profiles, from GPU-attached systems to dedicated storage hardware. We also build the federation layer that unifies these backends behind a simple interface and routes each workload to the right storage solution. About the Role You will help build the storage platform that powers OpenAI’s research and production systems. This is a hands-on infrastructure role for engineers who want to work on deeply technical systems at scale and own them in production. You’ll work across object storage, cross-region data movement, lifecycle management, and the federation layer that provides a unified interface across multiple backends. Much of our stack runs on Kubernetes, and we primarily build services in Rust. In this role, you will: Build and operate storage services that underpin OpenAI’s research infrastructure Develop object storage systems across cloud and in-house environments Build systems for cross-region data movement, replication, and recovery Design lifecycle management capabilities that keep data durable, available, and cost-effective Evolve the federation layer that unifies multiple backend systems behind a simple interface Improve performance, reliability, and operational excellence across the platform Collaborate closely with researchers and infrastructure teams to support rapidly evolving workloads You might thrive in this role if you: Have experience building or operating distributed systems in production Have worked on storage infrastructure, object stores, dist

The Team Platform Engineering is the department within SRE that is responsible for a range of critical infrastructure and operational functions that support the broader engineering organization. Among these are our multi-cloud-provider Kubernetes infrastructure, deployment machinery, and observability and alerting systems. The Fabric team manages the infrastructure that enables secure communication between systems and from the public internet. Their responsibilities encompass network architecture, service mesh, and edge load balancing, ensuring customer data remains safe in transit. The team plays a crucial role in developing and maintaining the reliable and globally connected multi-cloud network that supports MongoDB products. This role can sit in our NYC HQ, our smaller Austin, Palo Alto, or San Francisco offices, or fully remote from anywhere in North America. When based in an office, we provide hybrid work accommodation. Role Overview We are seeking a talented Site Reliability Engineer (SRE) with a strong networking background to join the Fabric team. This role is pivotal in building and maintaining the robust infrastructure necessary for secure and efficient communication between our services. As an SRE on the Fabric team, you will leverage your expertise in networking, distributed systems, and automation to ensure our systems are resilient, scalable, and reliable. The ideal candidate should Have 10+ years of experience working on software and operating distributed systems, with deep expertise in networking fundamentals and a good understanding of how the internet works, e.g. TCP/IP (including IPv6), DNS, TLS/mTLS, BGP, tunnels, overlays, and SDN principles Possess a customer-focused mindset, driving improvements that benefit end-users Value efficiency in processes and operations, and display a strong preference for automation over manual processes (“allergic to ops work”) Be intimately familiar with modern cloud-based infrastructure and the network design prim

Overview: The Data Acquisition team within the Foundations organization at OpenAI is responsible for all aspects of data collection to support our model training operations. Our team manages web crawling and GPTBot services and works closely with Data Processing, Architecture, and Scaling teams. We are looking for a skilled Software Engineer to join our Data Acquisition team. Responsibilities: Own and lead engineering projects in the area of data acquisition including web crawling, data ingestion, and search. Collaborate with other sub-teams, such as Data Processing, Architecture, and Scaling, to ensure smooth data flow and system operability. Work closely with the legal team to handle any compliance or data privacy-related matters. Develop and deploy highly scalable distributed systems capable of handling petabytes of data. Architect and implement algorithms for data indexing and search capabilities. Build and maintain backend services for data storage, including work with key-value databases and synchronization. Deploy solutions in a Kubernetes Infrastructure-as-Code environment and perform routine system checks. Conduct and analyze experiments on data to provide insights into system performance. Qualifications: BS/MS/PhD in Computer Science or a related field. 4+ years of industry experience in software development. Experience with large web crawlers a plus Strong expertise in large stateful distributed systems and data processing. Proficiency in Kubernetes, and Infrastructure-as-Code concepts. Willingness and enthusiasm for trying new approaches and technologies. Ability to handle multiple tasks and adapt to changing priorities. Strong communication skills, both written and verbal. 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

Overview: The Data Acquisition team within the Foundations organization at OpenAI is responsible for all aspects of data collection to support our model training operations. Our team manages web crawling and GPTBot services and works closely with Data Processing, Architecture, and Scaling teams. We are looking for a skilled Full-Stack Engineer to join our Data Acquisition team to build and optimize the interfaces and tools that power our data infrastructure. Responsibilities: Develop and maintain full-stack applications that support data acquisition, including internal tools and dashboards. Collaborate closely with cross-functional teams, including Data Processing, Architecture, and Scaling, to ensure seamless data ingestion and workflow management. Design and implement APIs to facilitate data interactions between internal services and external data sources. Enhance user experience by developing intuitive web-based interfaces for managing and monitoring data pipelines. Optimize backend services for performance, scalability, and security in a distributed computing environment. Work with legal and compliance teams to ensure our data acquisition processes adhere to privacy regulations and best practices. Deploy and maintain infrastructure using Kubernetes and Infrastructure-as-Code (IaC) methodologies. Analyze system performance, conduct experiments, and improve data workflows to maximize efficiency. Qualifications: BS/MS/PhD in Computer Science or a related field. 4+ years of industry experience in full-stack development. Proficiency in frontend frameworks (React, Vue, or similar) and backend technologies such as Python, Node.js, or Go. Strong expertise in RESTful APIs, GraphQL, and database design (SQL and NoSQL). Experience building data-intensive applications that handle large-scale datasets. Familiarity with cloud platforms (AWS, GCP, or Azure) and container orchestration (Kubernetes, Docker). Prior experience with web crawling and large-scale data processing is a

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. The Infrastructure team is central to this mission, setting the core strategy and implementing the vision. From site selection to deployment to operations, this team sits at the intersection of commercial, technical, and operational domains, interacting with experts and executives inside and outside of OpenAI. We design and operate mission-critical facilities that support cutting-edge AI workloads at scale. About the Role We are seeking a Facilities Operations Lead to support the commissioning, deployment, and long-term operation of our next-generation AI data centers. This role bridges the interface between data center construction and hardware landing, ensuring seamless integration of mission-critical infrastructure with hardware deployment timelines. You will define and execute commissioning plans, support infrastructure bring-up, and take ownership of operations and maintenance for cutting-edge, large-scale, AI data centers. You will collaborate closely with design, construction, and hardware teams to define repeatable processes for new data center builds and lead hands-on operations to uphold the performance and reliability of our deployed infrastructure. Key Responsibilities Define and execute sequences of operations, commissioning steps, and bring-up processes for mission-critical data center facilities. Interface with the design and hardware teams to define deployment procedures tailored to each data center and hardware configuration. Oversee installation, commissioning, and operational readiness of large-scale data center campuses. Manage monitoring, maintenance, and quality control of the data center infrastructure, including high-performance liquid cooling systems. Develop on-site operations staffing strategy. Develop and enforce procedures for planed and unplanned downtime and SLAs for critical

Experienced Engineering Technical Specialist Company: The Boeing Company Boeing Defense, Space & Security (BDS) is seeking Experienced Engineering Technical Specialists (Level 3) to join the team in Berkeley, MO. This position supports Risk Managed Framework compliance across multiple avionics test labs as well as the administration of embedded PCs and host PCs on avionics test benches. The Lab Infrastructure team is responsible for the design, modification, and troubleshooting of all test benches used in the avionics' lab to support systems integration testing on the F-15. Position Responsibilities Build and configure embedded PCs and host PCs on test benches Support RHEL 9 Installation, configuration, patching and maintenance of Linux server environments Support containerization Provide active directory management and file server management Troubleshoot user problems related to hardware, software, or processes Conduct monthly OS patching and anti-virus updates Create user accounts and reset passwords Run backups on workstations and servers Maintain compliance with Risk Managed Framework and NISPOM rules Keep facility signage up to date Maintain lab access list Travel may be required up to 10% of the time; domestically and/or internationally depending on business needs. This position requires an active U.S. Secret Security Clearance (U.S. Citizenship Required). (A U.S. Security Clearance that has been active in the past 24 months is considered active) Basic Qualifications (Required Skills/Experience) <ul

Cloud Platform Administrator (Mid-Level, Senior or Lead) **Sign on Bonus Potential** Company: The Boeing Company The Boeing Company’s Specialized United States Infrastructure Operations is currently seeking a Cloud Platform Administrator (Mid-Level, Senior or Lead) to join the team in Berkeley, MO; Seattle, WA; or Daytona Beach, FL . The Infrastructure team is seeking a skilled platform engineer to help build and operate the cloud platform services that host critical enterprise applications and software toolchains. In this role, the selected candidate will focus on the shared platform capabilities that enable teams to deploy, run, and maintain containerized and cloud-hosted solutions in a consistent and supportable manner. As both an individual contributor and technical leader, this position will help define and implement platform standards for Kubernetes, container hosting, deployment automation, configuration management, and operational support. This role is focused on platform reliability, repeatability, scalability, and service enablement, rather than custom application software development. Position Responsibilities: Design, implement, and maintain cloud platform services supporting Kubernetes, containers, ingress, storage integration, secrets management, and service connectivity Build and sustain reusable deployment patterns for Commercial-Off-The-Shelf (COTS), Open Source Software (OSS), and internally customized applications Develop and maintain automation for platform provisioning, upgrades, patching, and lifecycle support Manage cluster lifecycle activities including: Cluster upgrades Node management <

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