Workload Porting And Performance Engineer in United States

About the Team Our mission at OpenAI is to discover and enact the path to safe, beneficial AGI. To do this, we believe that many technical breakthroughs are needed in generative modeling, reinforcement learning, large-scale optimization, active learning, and other areas. The team builds the performance-critical systems that allow OpenAI's models to run efficiently across a diverse set of AI accelerators. We work across the inference stack, from low-level kernels and compilers through model execution, to unlock the full capabilities of the underlying hardware. About the Role As a Software Engineer, Trainium, you will help bring OpenAI's inference workloads to AWS Trainium and build the software stack required to run cutting-edge frontier models efficiently on the platform. This is a deeply technical, cross-stack role spanning kernels, compilers, and model execution. You will work on the systems needed to support OpenAI's inference stack on Trainium, including developing and optimizing high-performance kernels, improving compiler support, and enabling efficient execution of the model forward pass. You'll work closely with engineers across inference, compilers, kernels, and ML systems to identify performance bottlenecks and build the software needed to take full advantage of Trainium. The work may range from low-level hardware-specific optimization to compiler and runtime improvements to integrating new model architectures into the inference stack. If you enjoy working at the intersection of ML systems, compilers, kernels, and accelerator hardware, this role is for you. We're looking for engineers who are self-directed, comfortable operating across abstraction layers, and excited to solve challenging performance problems for frontier-scale AI systems. In This Role, You Will Build and optimize OpenAI's inference stack for AWS Trainium. Develop high-performance kernels for critical model operations and workloads. Extend and improve compiler support to efficiently target

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 a Product Engineer on the Dedicated Inference team, you'll shape the state-of-the-art developer experience for deploying and operating AI workloads in production. From the CLI and SDKs to APIs, observability, and debugging workflows, you'll build the tools customers rely on every day to manage mission-critical inference deployments. Few teams at Baseten have as much breadth and visibility as Dedicated Inference. The team is often at the forefront of new product development, giving engineers the opportunity to shape the experience of some of our most important customers. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Dedicated Inference team: Chains for multi-component workflows Asynchronous inference Model APIs for frontier models Model training built for production inference RESPONSIBILITIES Implement new features and products for the team Design ergonomic APIs and abstractions to solve customer problems Fix bugs and resolve customer issues with urgency Work across the stack - regardless of where you start, you’ll end up touching both React Components and Kubernetes Pods Work closely with the product and forward deployed engineering teams to develop and drive new product ideas REQUIREMENTS Bachelor's degree or higher in Computer Science or related field Proficient coding abilities in one or more popular programming or scripting languages; Python, Go, or Javascript proficie

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 OPPORTUNITY We are looking for Senior Software Engineers to join our team. This is a specialized, high-impact role sitting at the intersection of high-performance computing (HPC) and Large Language Model (LLM) engineering. You will not just be building the automated "speedometer and diagnostic" suite for our next-generation AI infrastructure; you will be defining the roadmap, driving key technical decisions, and taking full ownership of the future of this work. RESPONSIBILITIES Benchmarking : Evaluate, run and automate standard LLM quality benchmarks (GSM8K, MMLU) alongside custom performance suites for specific workloads (e.g., long-context window, KV cache reuse, disaggregated serving). DevEx Improvement : Develop and maintain internal GPU-enabled development environments (similar to GitHub Codespaces). You will ensure the team has seamless, high-performance "dev machines" optimized for model experimentation. Tool Development : Build and contribute to open-source tools such as InferenceMAX and genai-bench to automate model evaluation, benchmarking and analysis. System Profiling : Use profilers like PyTorch Profiler, NVIDIA Nsight Systems and py-spy to collect performance profiles, identify bottlenecks, and debug the compute/networking stack. Monitoring & Observability : Develop real-time dashboards and alerts to monitor system health, model startup times, and runtime performance. Continuous Integration : Auto

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. We are looking for a Security Operations Lead (SOC Lead) to build, mature, and operate our 24/7 detection and response capabilities across a modern cloud-native and AI-driven environment. This role leads the global SOC function—monitoring, SIEM ownership, detection engineering, alert triage, and operational readiness—while also evaluating and integrating emerging AI-based SOC products and autonomous response platforms . You will oversee monitoring across multi-cloud environments (GCP primary, AWS/Azure secondary), Kubernetes, SaaS services, endpoints, developer tools, and AI workloads . You’ll collaborate closely with Cloud Security, Compliance/GRC, SRE, Platform Engineering, IT/Endpoint teams, and AI Infrastructure to ensure our detection strategy scales and stays ahead of evolving threats. This is a hands-on leadership role perfect for someone who wants to shape the SOC of the future while solving complex challenges in a high-scale AI setting. What You’ll Do SOC Leadership & 24/7 Monitoring Lead, mentor, and scale a global SOC team responsible for 24/7 monitoring, alert intake, triage, correlation, and escalation. Build operational rigor: processes, runbooks, SLAs, metrics, and quality standards for high-scale environments. Cover monitoring across: Cloud infrastructure (GCP, AWS, Azure) Kubernetes/GKE/EKS/AKS clusters SaaS platforms (Google Workspace, GitHub, Slack, Okta, etc.) Endpoints (macOS, Linux, Windows) including EDR/XDR telemetry Developer platforms + CI/CD pipelines AI/ML systems and model-serving workflows AI-Based SOC Integration & Innovation Evaluate, adopt, and integrate AI-native SOC technologies for triaging, detection, and correlation Identify opportunities to automate triage, investigations,

Location Details: At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.​ This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. Join Our Team… GoDaddy's Global Storage Engineering team operates one of the largest Ceph environments in the industry, powering the object, block, and file storage platforms that underpin hosting, applications, internal infrastructure, and next-generation AI/HPC workloads. If you're passionate about distributed systems, large-scale storage architecture, and solving complex reliability challenges, you'll work on infrastructure that few engineers ever experience. At GoDaddy, Ceph isn't a side project — it's a critical platform. Our environment spans 80+ production clusters, 20,000+ OSDs, and approximately 300 PB of raw storage capacity, supporting tens of billions of objects across multiple continents. The scale demands deep technical expertise in storage architecture, automation, observability, and performance engineering. As a Senior Site Reliability Engineer, you'll be a key technical owner of the platform, responsible for maintaining reliability, driving operational excellence, and influencing the future evolution of our storage ecosystem. You'll tackle challenging production problems, develop automation that operates at massive scale, contribute to architectural decisions, and collaborate with some of the industry's most experienced Ceph engineers. This is an opportunity to have direct impact on a storage platform that serves millions of customers worldwide. What You'll Get to Do… Own the reliability, performance, scalability, and capacity of large-scale production Ceph environments supporting object, block, and file storage wor

Location Details: At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.​ This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. Join Our Team GoDaddy's Global Storage Engineering team operates one of the largest Ceph environments in the world, delivering the object, block, and file storage platforms that power GoDaddy's hosting infrastructure, internal services, OpenStack environments, and next-generation AI/HPC workloads. If you're passionate about distributed systems, storage architecture, and solving failure scenarios at massive scale, this is an opportunity to work on infrastructure few engineers will experience in their careers. Ceph is a strategic platform at GoDaddy — not an ancillary service. Our global footprint includes 80+ production clusters, 20,000+ OSDs, 1,830 storage nodes, 300 PB of raw capacity, and 69 billion objects spanning five datacenters across three continents. The platform supports RBD, RGW (S3/Swift), and CephFS workloads through more than 1,550 pools, 574,000 placement groups, and 900+ MDS daemons, creating engineering challenges that demand deep expertise in storage architecture, data durability, performance optimization, automation, and observability. As a Lead Senior Site Reliability Engineer, you'll serve as one of the principal technical leaders for GoDaddy's Ceph platform. You'll design the next generation of storage clusters, lead major platform upgrades, drive capacity and hardware strategy, and establish the standards that govern how the platform scales. You'll be the engineer the team turns to for the most complex s

The ML Observability team builds cutting-edge tools to monitor, explain, and improve AI systems in production, particularly those leveraging Large Language Models (LLMs) and generative AI. We provide robust, scalable observability for AI workloads, including drift detection and model evaluation, and behavior tracing, enabling customers to ship AI with confidence. As a Staff Engineer, you’ll lead the development of new features and foundational capabilities within Datadog’s LLM Observability product. You will shape product direction, drive experimentation, and apply your deep understanding of both AI systems and software engineering to solve open-ended problems in the fast-moving AI landscape. Your work will directly impact how our customers monitor, troubleshoot, and optimize LLM-based applications in production. Join us in building the foundational tools that make AI systems observable, understandable, and reliable in the real world. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Drive design and implementation of LLM observability features. Ideate, prototype, and scale new product features to provide insights and drive improvements for generative AI systems Work cross-functionally with other eng teams, product, UX, and applied science to iterate fast and find product-market fit Develop and extend tools for tracing, evaluating, and debugging LLMs Influence architecture decisions and mentor engineers to build resilient, high-performance systems Stay close to customer pain points and use those insights to guide product and engineering priorities Stay current with industry trends and advancements in machine learning and observability, driving innovation within the team Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or r

We are Datadog's in-house product experts. The Datadog Federal Support Engineering team is dedicated to serving as highly trusted technical advisors for our Public Sector customers, who operate within some of the most highly regulated and security-constrained environments. These customers include various government agencies and organizations with critical, sensitive missions. As a Federal Support Engineer 3, this role places you at the forefront of supporting these customers' mission-critical workloads. These complex workloads are often deployed across sophisticated hybrid and multi-cloud architectures, requiring deep expertise in cloud technologies, monitoring, and security best practices. Your primary responsibility is to ensure the complete success of these customers across their entire lifecycle with Datadog. Whether you’re looking to learn from the best or be the best, the Federal Support team is dedicated to furthering personal development and team success. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Engage with public sector customers via multiple channels (ticketing system, live chat, calls, and screensharing tools) to identify and resolve technical support requests. Troubleshoot, investigate, and resolve complex technical issues in highly constrained environments across Datadog's 1000+ integrations, often with limited logs or sanitized data. Handle urgent escalation cases that may result in customer-facing troubleshooting calls, and internal or external incident management Become a subject matter expert in many Datadog product areas Partner with Product, Engineering, and Account teams to to validate bugs and advocate for customer-impacting improvements Provide mentorship to junior members of the team and serve

Join the MongoDB Server Query Optimization team, and help us build a world-class distributed open-source query optimizer. Our team plays a crucial role in the experience and performance of data processing. We are responsible for the MongoDB Query Language and the lifecycle of each query, through parsing, optimization and plan selection. We have a presence across the US and Europe including New York, Dublin, Seattle, Palo Alto, and Chicago. We support office-based and remote work and align projects with convenient work hours for each time zone. We have tons of interesting problems to solve with a direct impact on users for transactional, time-series, and analytical workloads. The team is endeavoring to systematically rewrite every major component of our optimization and execution systems. We need your help to design and build the heart of a distributed, flexible schema, document database. ​​This role can be based out of our US offices or remotely in the North America region. Candidate Profile 10+ years of experience in data management systems, distributed systems, or large-scale backend engineering Experience with building production-level code with a large user base, robust design structure and rigorous code quality Degree in Computer Science or similar field, or equivalent practical experience, with strong competencies in data structures, algorithms, and software design/architecture Experience with large code bases written in C++ or another systems programming language. You'll need to trace down defects, estimate work complexity, and design evolution and integration strategies as we rewrite different components of the system A strong foundation in core database internals is essential. While direct experience in query optimization is a massive bonus, it is not a prerequisite. We are also excited to meet candidates with strong backgrounds in compilers, language transpilers, or distributed storage systems Position Expectations Innovate in the area of flexible schema d

Join the MongoDB Server Query Execution team, and help us build a world-class distributed open-source database. Our team plays a crucial role in the performance and efficiency of MongoDB's data processing. We are responsible for building and improving the core execution engine that powers all queries, taking a logical query plan produced by the optimizer and turning it into reality. This includes developing the physical operators for data retrieval and manipulation, improving the runtime for complex analytical and transactional workloads, and owning critical components such as our new execution engine. In addition to the core server, we support the query execution needs of other major products like Atlas Streams, Atlas Search and Vector Search, and mongosync, making our work vital to the entire MongoDB ecosystem. You will be joining a globally distributed team with a significant presence in both North America and Europe. While this role is based in the NAMER region, you will regularly collaborate closely with colleagues across different time zones. We support both office-based work in our North America hubs like New York, as well as remote work. We have tons of interesting problems to solve with a direct impact on users for transactional, time-series, and analytical workloads. To meet the ever-increasing data demands of modern applications, we are actively evolving our query system; this includes strategically re-architecting and improving key components of our query execution engine. We need your help to design and build the core of a distributed, flexible schema document database. This role can be based out of one of our North America offices, such as NYC or Palo Alto, or remotely across North America. Candidate Profile 10+ years of hands-on, professional experience in query engine development or database internals Experience with building production-level code with a large user base, robust design structure and rigorous code quality Degree in Computer Science or

MongoDB is hiring a Staff Product Marketing Manager to build and own our go-to-market narrative for the Public Sector vertical, with a focus on Federal Government and the broader public sector market. This is a foundational hire for MongoDB’s Industry Verticals product marketing function: you will define how MongoDB’s unified data platform, spanning cloud, on-premises, and hybrid database deployments with integrated, production-ready AI capabilities, shows up for government buyers. You’ll turn a major compliance milestone into a durable competitive differentiator: developing the positioning, messaging, and sales-ready content that helps government agencies, systems integrators, and cloud/public-sector resellers understand why MongoDB is the right data platform for mission-critical, regulated workloads. You do not need prior government or public-sector work experience to succeed in this role — you need to be an excellent product marketer who can get fluent in a new domain quickly and partner closely with the compliance, product, and sales experts who already are. This role can be based in one of our MongoDB hub offices in the U.S. or remotely in the U.S. What you’ll do Own positioning and messaging for MongoDB’s Public Sector go-to-market, leading the federal GTM and launch related activities Translate MongoDB’s data platform capabilities — document database, search, vector search, stream processing, and integrated AI — into mission-relevant outcomes and value propositions for government buyers and the systems integrators who serve them Partner with Compliance, Security, Industry Solutions and Product teams to accurately represent related certification requirements in external-facing content, staying current as MongoDB pursues additional authorizations (e.g., DoD Impact Levels) Build the public sector sales enablement toolkit: battlecards, pitch decks, discovery guides, ROI/value models, and competitive intelligence tailored to federal buying processes and procuremen

About the Team The Industrial Compute team is responsible for building the physical infrastructure that powers OpenAI’s largest-scale AI systems. We design, deploy, and operate next-generation compute infrastructure across a rapidly expanding global footprint, combining OpenAI-owned infrastructure with strategic cloud and infrastructure partners to support frontier AI workloads. As our infrastructure footprint grows, operational excellence across third-party providers becomes increasingly critical. Our team ensures external infrastructure partners consistently deliver the reliability, performance, and operational maturity required to support OpenAI’s rapidly expanding compute environment. About the Role We are seeking a Hardware Technical Program Manager, Infrastructure Partner Operations to lead operational delivery across OpenAI’s third-party infrastructure partners, including major cloud service providers and strategic compute vendors. In this role, you will serve as the primary operational program manager for external infrastructure partners, driving accountability for service delivery, operational readiness, incident management, performance reporting, and continuous operational improvement. You will work closely with partner engineering and operations teams while coordinating internally across Hardware Engineering, Infrastructure Operations, Capacity Planning, Networking, Supply Chain, Deployment, Reliability Engineering, and executive leadership. Success in this role requires someone who understands how hyperscale infrastructure organizations operate, can establish strong operational governance with external partners, and is comfortable driving complex technical programs without direct ownership of the underlying infrastructure. Key Responsibilities Own operational engagement with third-party infrastructure providers, ensuring consistent execution against operational commitments, service-level agreements (SLAs), and performance expectations. Develop operationa

About the Team OpenAI’s Infrastructure Operations team is responsible for the availability, reliability, and operational excellence of one of the world’s largest AI infrastructure networks. The team owns day-to-day operations of production AI networks across Industrial Compute's data centers, working with colocation providers, deployment teams, and hardware vendors to deliver highly available GPU infrastructure for AI training and inference workloads. About the Role We are seeking an Infrastructure Operations Engineer to operate and improve the large-scale Ethernet fabrics that support GPU clusters, storage systems, and management infrastructure. This role combines hands-on production operations with automation, observability, and incident response across a global AI network. The ideal candidate has experience operating high-availability data center, cloud, AI, or HPC networks and can move comfortably from physical-layer troubleshooting to routing and fabric behavior, change execution, and root-cause analysis. You will partner closely with network architecture, systems engineering, GPU engineering, storage engineering, security, deployment, site operations, service providers, colocation partners, and hardware vendors to raise reliability and reduce operational toil. Key Responsibilities Own the operational health, availability, and reliability of production AI network infrastructure across Industrial Compute's data centers. Monitor, troubleshoot, and resolve network incidents while meeting service-level objectives (SLOs), reducing Mean Time to Detect (MTTD), and minimizing Mean Time to Recovery (MTTR). Operate and maintain large-scale Ethernet fabrics supporting GPU compute, storage, and management networks. Execute production network changes, maintenance windows, and capacity expansions with minimal customer impact. Manage the hardware lifecycle, including switch and optics replacements, RMA coordination, software upgrades, and preventive maintenance. Support new A

About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in cloud-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including cloud-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re looking for a backend engineer who can quickly understand OpenAI’s models, products, and systems, then adapt first-party deployments for other cloud platforms. You’ll build backend services, APIs, SDK integrations, authentication flows, and cloud service infrastructure that let developers use OpenAI capabilities in the cloud environments where they already build. This role involves working across teams, sometimes embedded with partner product groups, to ship products quickly and across multiple platforms at the same time. It’s a strong fit for engineers who have built developer tools, especially AI-powered tools, communicate clearly across technical boundaries, and can shape architectures that support different deployment models; experience building cloud services is a strong plus. In this role, you will: Build backend and infrastructure systems that extend OpenAI’s API platform into cloud-native environments, like AWS. Design and ship cloud-contained products that allow customers to use OpenAI capabilities while keeping workloads and data within cloud environments. Help stand up cloud-hosted Codex experiences powered by the OpenAI Responses API. Build the infrastructure and runtime abstractions

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