Software Reliability Engineer in United States

Power and Performance Validation Engineer 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 Reporting to senior leadership within Architecture and Validation, the Power and Performance Validation Lead will drive validation strategy and execution for advanced AI compute silicon and systems. The role is responsible for leading power, thermal and performance validation activities across pre-silicon and post-silicon environments to ensure products meet efficiency, reliability and scalability expectations. This role requires strong technical expertise and collaboration across multiple engineering disciplines to deliver robust validation methodologies, scalable automation frameworks and actionable performance insights. The Team The Power and Performance Validation team sits within the Architecture and Validation organisation and is responsible for validating the performance, efficiency and thermal behaviour of Graphcore silicon and systems. The team supports the full product lifecycle, from early architectural modelling through to first silicon bring-up, characterization and production readiness. Engineers work closely with cross-functional teams globally to debug compl

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. Responsibilities and Duties We are seeking a highly skilled System Tests & Diagnostics Engineer to develop, extend, and integrate specialized silicon validation and diagnostics tools for next-generation AI SoCs. Unlike traditional validation roles focused on executing test plans, this position is responsible for developing the diagnostic software and stress tools that expose hardware failures, characterize silicon behavior, and improve platform observability throughout bring-up and validation. You will work closely with Arm engineers to understand and extend existing diagnostics technologies while developing Graphcore-specific capabilities for future AI hardware. Role Summary You will work with existing Arm-developed diagnostics technologies and extend them to support Graphcore's next-generation AI silicon. You will be responsible for developing system-level diagnostics and stress tools that integrate with an existing framework to detect data integrity, computational correctness, performance, and reliability issues across CPUs, AI accelerators, memory, storage, PCIe, firmware, BMC, and other platform components. Examples include silent data corruption (SDC) tests, power transient stress tools, and platform diagnostics, with opportunities to develop new diagnostics as future hardware capabilities evolve. This role requires close collaboration with hardware architects, firmware enginee

Staff -Power and Performance Validation Engineer 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 Reporting to senior leadership within Architecture and Validation, the Power and Performance Validation Lead will drive validation strategy and execution for advanced AI compute silicon and systems. The role is responsible for leading power, thermal and performance validation activities across pre-silicon and post-silicon environments to ensure products meet efficiency, reliability and scalability expectations. This role requires strong technical expertise and collaboration across multiple engineering disciplines to deliver robust validation methodologies, scalable automation frameworks and actionable performance insights. The Team The Power and Performance Validation team sits within the Architecture and Validation organisation and is responsible for validating the performance, efficiency and thermal behaviour of Graphcore silicon and systems. The team supports the full product lifecycle, from early architectural modelling through to first silicon bring-up, characterization and production readiness. Engineers work closely with cross-functional teams globally to debu

About the Team pAGI Infra team builds and operates the systems that make large-scale model training and evaluation reliable, efficient, and easy to run. Our work spans distributed training infrastructure, inference and grading platforms, compute scheduling, and research tooling. We partner closely with researchers and engineering teams to turn new research needs into dependable infrastructure, improve GPU efficiency, and shorten the path from an experiment to a validated model. About the Role We’re looking for an AI Systems Engineer to help scale the infrastructure behind our training and evaluation workflows. You’ll own projects from identifying bottlenecks and designing solutions through deployment and operation. The work combines distributed systems engineering, performance optimization, and close collaboration with researchers. You might build a shared grading service, improve resource allocation across workloads, or bring a new training stack into production — directly improving how quickly and reliably research moves forward. In this role, you will: Build and operate infrastructure for large-scale training and evaluation, improving reliability, throughput, and resource efficiency. Develop shared inference and grading platforms with automated capacity management, health monitoring, and visibility into performance. Improve compute scheduling and resource allocation to reduce idle GPU time and help workloads recover quickly from failures. Diagnose bottlenecks across training, inference, and orchestration, and work across teams to improve end-to-end performance. Build self-service tools, automated validation, and observability that help researchers launch experiments, diagnose issues, and compare results with less manual intervention. You might thrive in this role if you: Are excited about the potential of personal AGI and want to build the infrastructure that enables it. Have strong software engineering fundamentals and experience building or operating large-scal

About the Team OpenAI's People team helps hire, develop, and support the people building safe and beneficial AGI. Within that team, People Systems builds the technical foundation that enables our HR, recruiting, payroll, benefits, and performance operations to scale with quality, speed, and rigor. We work at the intersection of HR systems, software engineering, and internal tooling. Our goal is not just to keep core systems running, but to build durable technical leverage for the company. About the Role We're hiring a Workday Engineer to help design, build, and operate the systems that power critical people workflows at OpenAI. This is a highly technical role for someone who combines strong Workday expertise with real engineering fluency. You'll build reliable integrations, improve system architecture, automate complex workflows, and help connect Workday to internal tools, external platforms, and emerging AI-driven systems. You should be comfortable going beyond configuration work. We're looking for someone who can reason through ambiguous systems problems, write and debug technical solutions, work effectively in Git-based environments, and use modern developer workflows, including CLI-driven tooling, to build and operate with speed and discipline. You'll partner closely with cross-functional teams across People, Finance, Security, and Engineering, including our People Innovations team, to build systems that are secure, scalable, and practical. Some work will involve improving mature production infrastructure; some will involve building entirely new workflows and capabilities from scratch. In this role, you will Design, build, and maintain Workday integrations, applications, and workflow automations across domains such as payroll, benefits, recruiting, performance, and case management Improve the reliability, quality, and scalability of People systems through strong engineering, testing, and operational practices Build technical solutions that connect Workday with i

Interactive Design Engineer - HPIQ Description - About The Role As a Product Design Engineer at HP IQ, you’ll work at the intersection of creativity, engineering, and design to develop groundbreaking devices that redefine how people interact with technology. You’ll collaborate closely with industrial designers, hardware engineers, and interaction designers to transform ideas into functional prototypes and production-ready designs. From 3D CAD modeling and hands-on prototyping to engineering analysis and design validation, you’ll help solve complex mechanical challenges and drive designs from early concepts toward production. You’ll have the opportunity to take ownership of meaningful engineering work while learning from an experienced, multidisciplinary team and contributing to products that push the boundaries of what’s possible. What You Might Do Design mechanical parts, components, and assemblies for new consumer devices using 3D CAD (NX) Create detailed 2D engineering drawings, define specifications and tolerances, and work closely with overseas vendor partners to ensure accuracy and quality Design and run experiments, applying engineering analysis and test results to guide design decisions Evaluate materials, manufacturing processes, and design tradeoffs to develop robust and scalable solutions Work cross-functionally with hardware, software, industrial design, and other engineering teams to bring concepts from ideation through development Conceptualize, design, and build prototypes that quickly validate ideas Participate in design reviews, clearly communicating design decisions, technical analysis, and tradeoffs to both technical and non-technical audiences Build, test, troubleshoot, and iterate prototypes to identify issues and improve product performance, reliability, a

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and establish teams with the most thoughtful people in the world. We are looking for an excellent engineering manager to own and deliver an end to end manageability stack for Data Center Systems. We are seeking an experienced manager who is deeply technical, hands-on, and has a wide system view. You will manage a team of experts, design & build OpenBMC based manageability software stack for NVIDIA’s next generation Data Center Compute Systems. We want to grow our teams with the smartest people in the world. If you're creative and autonomous, we want to hear from you! What you’ll be doing: Own and deliver OpenBMC based manageability stack for next generation Data Center Compute Systems. Own firmware delivered to data centers in terms of quality, reliability and telemetry performance. Manage and lead a distributed team of software engineers to deliver firmware stack with high quality. Work with data center architects and cloud customers for correct requirements and scope implementation to ensure speed of light product development. Work closely with cross functional teams to ensure scalable manageability architecture for all data centers products Drive efficiency, reliability and optimization in firmware architecture from a data center view point. Work closely with customers and internal teams to resolve issues at Speed of Light. What we need to see: BS, MS, or PhD in EE/CS or related field o

About Datadog: We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale—trillions of data points per day—allowing for seamless collaboration and problem-solving among Dev, Ops and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Team: The Revenue Data Engineering Teams designs, builds and runs the data pipelines and helper systems to accurately and in a timely manner quantify our customers’ usage across all Datadog products. This team is at the leading edge of any new product we release. The Revenue Data Processing team builds and operates the data pipelines that does billing, and cost attribution for all Datadog products. We process terabytes of data daily to power revenue-critical systems and are at the center of every new product launch at Datadog. As a Senior Software Engineer, you will own meaningful parts of a large-scale, mission-critical processing platform — driving architectural improvements, building new billing capabilities, and maintaining the high reliability bar our downstream consumers depend on. You Will: Design and build high-throughput data pipelines for billing and cost attribution Drive platform improvements — latency reduction, Spark optimization, sharding, and cross-datacenter reliability Own root-cause investigations on billing accuracy issues in collaboration with Finance and Product teams Contribute to new billing features Work across Python and Scala, with technologies including Spark, Airflow, Trino, and Apache Iceberg Participate in on-call rotation and maintain a high reliability bar for production systems Contribute to engineering standards and help grow the technical culture of the team You Are: You have significant experience building and operating production data pipelines at scale using Spark and Airflow

Datadog’s Cloud Networks team designs, builds, and maintains the production network infrastructure that powers everything built on top of our platform across AWS, GCP, Azure, and beyond. In this role, you’ll set technical direction for how we scale our multi-region, multi-cloud network footprint while keeping reliability and performance high. You’ll partner closely with internal teams and Cloud Service Providers to troubleshoot complex connectivity issues, integrate new networking capabilities, and improve the foundations our engineers and customers rely on. This is a high-impact opportunity to drive meaningful improvements in scale, resiliency, and cost efficiency. 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: Design, build, and operate cloud network infrastructure across AWS, GCP, Azure, and Neoclouds in a multi-region environment. Own connectivity between clouds, customers, and developers—ensuring scalable, secure, and reliable network paths. Set clear technical direction for expanding data centers and evolving the network while maintaining stability and performance. Improve cross-site and cross-region connectivity patterns to support Datadog’s growing platform needs. Lead deep investigations into latency, packet loss, and connectivity failures – from pcap and path analysis through to escalations with cloud providers that may originate from customer support Identify and deliver network-related efficiency and cost-saving opportunities that positively impact business health. Who You Are: You have deep networking expertise. You understand BGP, route policies, path selection, prefix advertisement, and what breaks in large-scale networking. You have substantial experience designing, building, and evolving large-scale Software-Defined Networks—inclu

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. Snowflake is expanding the boundaries of the Data Cloud to support mission-critical transactional workloads. Our goal is to deliver OLTP capabilities with the performance, reliability, simplicity, and scale customers expect from Snowflake, while creating a seamless experience across transactional and analytical data. We are looking for a Senior Engineering Manager – OLTP to lead engineering teams and leaders building core transactional database technology and the cloud infrastructure required to operate it at scale. You will help define the architecture and roadmap, grow the organization, and drive technology from design through production. AS A SENIOR ENGINEERING MANAGER – OLTP AT SNOWFLAKE, YOU WILL: Set technical and execution strategy for key areas of Snowflake's OLTP platform, translating product goals into architecture, roadmaps, and team plans. Lead and grow multiple engineering teams, developing managers and senior technical leaders while fostering a culture of ownership, technical excellence, and execution. Drive adoption of AI and agentic development practices to improve engineering velocity, quality, and productivity across the software development lifecycle. Drive architecture and technical decisions in areas such as transactions, concurrency control, low-latenc

Job Details: Job Description: Join an enthusiastic team of engineers in Intel's Networking Solutions Group (NSG) focused on enabling next generation of programmable Infrastructure Processing Units (IPUs) with our lead customers as part of the Customer Experience Support (CES) organization. Intel brings decades of leadership in networking, virtualization, packet processing, storage, and security to a new class of IPU products that accelerate host networking functions and support emerging use cases such as security, virtualization, storage, load balancing, and data path optimization. Working closely with major cloud service providers and Intel development teams, you will help deliver customized IPU based solutions that enhance isolation, security, performance, storage and system management for our customers. A big part of the day-to-day job is to help customers manage feature request processes, enable solutions, and debug issues. Projects and responsibilities include but are not limited to: • Gain our customers' trust, understand their needs, and build POCs to meet them. Work closely with internal and external partners to understand use cases and requirements. • Be the go-to technical resource for customers building complex Datacenters, AI infrastructure as well as helping them understand performance characteristics for solutions. • Prepare and deliver technical content to customers including presentations, workshops, etc. • Contribute across the full IPU lifecycle, including board and platform bring up, low-level device initialization, OS driver and kernel configuration, system management, feature enablement, use case testing, debugging, and verification. • Defines systems implementation and integration solutions and plans to ensure optimum performance and reliability across hardware, firmware and software w

Are you ready to contribute to world-class innovation and push the boundaries of what's possible? At NVIDIA, you'll have the opportunity to be part of a team that is driving groundbreaking impacts across various markets. As a Thermal Solutions Development Engineer, you will play a pivotal role in our Silicon Codesign Group, transforming thermal solution concepts into lab-ready builds and beyond. What you will be doing: Build thermal solutions for engineering characterization and validation of next-gen GPU/SOC products, ensuring flawless delivery from concept to lab. Drive end-to-end development and deployment of thermal solutions, collaborating with internal teams and external vendors on build requirements, prototype evaluation, test system integration, and software automation. Improve thermal design processes by incorporating feedback and findings, developing workflow and maintaining our world-class standards. Work closely with system architects, chip and board designers, and software/firmware engineers in a dynamic and high-energy environment to bring industry-defining products to market. Apply AI-enabled approaches and AI tools to accelerate design iteration, test planning, and characterization/validation triage (e.g., requirements/spec summarization, experiment prioritization, log/telemetry summarization, anomaly/outlier detection), improving cycle time, coverage, and traceability while validating outputs against physics, specs, and lab measurements. Partner with AI/tooling teams as the thermal domain SME to define use-cases, success criteria, and evaluation methods; provide feedback to improve tool reliability and usability. What we need to see:

NVIDIA is seeking a Senior System Architect: Heterogeneous EDA Systems to solve a complex challenge in accelerated computing: Failure Attribution at Scale. As EDA or equivalent experience workloads scale across thousands of heterogeneous nodes, a single failure can cause massive resource waste. We need an engineer to develop and build an automated framework. This framework will ingest telemetry from CPU and GPU clusters to identify the root cause of job failures in real-time. It will distinguish between hardware faults, infrastructure instability, and software defects. What you'll be doing: Architect Failure Attribution Frameworks: Build a scalable "flight recorder" for EDA jobs that captures high-fidelity state across the CPU, GPU, and Fabric at the moment of failure. Build automated diagnostics that correlate GPU XID errors, PCIe bus failures, and CUDA memory exceptions. Connect these errors with system-level events such as OOM kills or NUMA-related hangs. Distributed Logging & Tracing: Implement low-overhead tracing mechanisms (using tracing tools or custom agents) that provide access to job execution across multi-node Slurm or Kubernetes clusters. Root Cause Automation: Develop heuristics and models based on machine learning to classify failures as "Hardware Fault," "Software Bug," or "Environment Issue." This reduces the Mean Time to Identify (MTTI) for R&D teams. Resiliency Engineering: Work closely with hardware and infrastructure teams to define "signals of impending failure," enabling proactive job migration or check-pointing before a crash occurs. What we need to see: Distributed Systems Mastery: BS, MS, or PhD in Computer Science or Electrical Engineering (or equivalent experience) with 6+ years in systems programming. Experience building automated

Join VTS as an Engineering Manager. As a technical leader, you'll drive high-impact, customer-facing projects across major features in web and mobile. You’ll play a pivotal role in advancing VTS's evolution into an AI-powered platform, further cementing our industry-leading position. In this role, you will be responsible for fostering a healthy and collaborative culture, guiding the team's execution and delivery, and mentoring engineers to grow their careers and capabilities. ** Please note that this opportunity is located in New York, NY, and requires this hire to work from our office 4 days a week. ** To thrive in this role, you have: Proven experience leading software teams using agile development methodologies. A strong technical background with a proven track record of building, deploying, and maintaining scalable web applications, services, and third-party integrations. Experience working on high-impact, business-critical domains, where reliability, performance, and operational stability are essential. Demonstrated ability to recruit and develop talent, strengthening the team's capabilities through effective coaching and mentorship. The ability to engage in strategic technical discussions, adeptly manage technical tradeoffs and risks, and ensure alignment with product and business goals, especially in environments involving multiple systems and external partners. A sense of empathy for the customer and a relentless focus on shipping high-quality products. Excellent communication skills that empower you to effectively convey ideas, coach, mentor, and educate others. A keen interest in building AI-backed features and leveraging AI as an engineering productivity tool. What you'll do: Lead and Develop a High-Performing Team : Foster a healthy, collaborative, and diverse culture that reflects our company and engineering values. Coach and mentor individual team members, creating a structured environment and feedback loop that supports career development and hi

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 are seeking a strategically-minded, technology-focused, and customer-centric Engineering Manager to lead one of our Infrastructure teams here. You will lead a team responsible for building, operating, and scaling the cloud infrastructure and platform systems that underpin CLEAR’s services, ensuring reliability, performance, and security across our environments. A successful candidate brings strong experience in cloud infrastructure, distributed systems, and operational excellence, along with a solid foundation in software engineering. You are an effective communicator who can lead complex infrastructure initiatives from inception through delivery, and thrive in fast-paced environments. This role requires a focus on building resilient, scalable systems, driving automation, and leading and developing high-performing engineering teams. What you'll do: Hire, develop, and grow engineering talent through coaching, mentorship, performance management, and career development planning Set clear goals and expectations, provide regular feedback, and foster accountability across the team Own and execute the roadmap for cloud infrastructure and platform engineering, and reliability initiatives Design, build, and operate a scalable, secure, and highly available cloud platform infrastructure Drive automation across infrastructure provisioning, deployment, and operations to improve efficiency and reduce manual overhead Establish and enforce best practices for system reliability, observability, incident response, and disaster recovery Partner with eng