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 looking for an experienced System Level Test Engineer to join our Product Test and Diagnosis Department (PTD). In this role, you will contribute to the development and deployment of System Level Test (SLT) solutions for next-generation AI processors. Working closely with hardware, software, validation, and manufacturing teams, you will develop test content, automation, diagnostics, and characterization capabilities that support silicon bring-up, yield learning, and manufacturing deployment. The ideal candidate will have strong technical foundations in semiconductor test and validation, excellent debug skills, and a passion for improving product quality and manufacturability. The Team The Product Test and Diagnostics team’s role is to detect and manage hardware defects that arise from the manufacture and use of our products. This covers chips, boards and finished systems and takes place both in the manufacturing sites and in the field. Responsibilities and Duties Develop and maintain SLT test content, automation, d
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Silicon Physical Design Engineer Multiple roles across different levels Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. 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. We are opening a new AI Engineering Campus in Bengaluru which will play a central role in Graphcore's work building the future of AI computing. The physical design team sits within the wider silicon design team which includes RTL, verification and DFT. Our work also involves strong links with architecture, packaging and product engineering. We are responsible for working with those teams to create high-quality RTL and building the final chip layout (e.g. GDSII) ensuring a signoff-quality design is delivered to the Foundry (e.g. TSMC). We are looking to hire high-quality silicon physical design engineers to join our team. The successful candidate will support the team with achieving our goals and creating the right engineering solutions. We are a collaborative team and good communication is essential, as is the ability to adapt and learn. For the successful candidate we offer an open, honest and collaborative environment working on leading-edge designs at the most advanced nodes. Our engineers are not siloed, and they are trusted and encouraged to ta ke ownership of their designs and problem solutions. You will be part of a team that looks for improvements to everything we do: our designs, our flows, our methodologies, our infrastructure. Responsibilities and Duties Applicants will be expected to contribute technically to the development of Graphcore's next generation of AI superchips, fo
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, Seattle, Washington D.C., Raleigh, London, and Amsterdam. The Data team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s unique network data to identify and stop fraud before it happens. The team owns the full ML lifecycle—from feature pipelines and model training to production serving and monitoring—building reliable, scalable systems that deliver high-quality fraud detection as we grow to support hundreds of customers. As a Senior Machine Learning Engineer, you will own the development of high-performance feature computation and online inference pipelines that power production machine learning systems at scale. You’ll build robust observability, monitoring, and automated debugging capabilities, while leveraging AI-assisted tools to investigate complex system behavior and maintain high reliability. You’ll partner closely with ML Infrastructure, Data Science, and Product teams to execute critical technical initiatives and deliver scalable, high-impact ML solutions. Responsibilities: Build and scale machine learning systems that power a rapidly growing fraud detection product in a fast-paced environment. Solve complex technical challenges at the intersect
At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the Role Anyscale's product security needs are growing as we ship to larger and more demanding customers. We're looking for a Senior Product Security Engineer to own our secure software development lifecycle and to be engineering's partner on building security into the product. Reporting to the Head of Security, you will work in close partnership with engineering. This is a senior, high-ownership role. You will own and operate a scalable SSDL, partner with engineering on security features and secure design, review the security of existing systems and new initiatives, and own how we find, track, drive to resolution and report on vulnerabilities in what we ship. This role is based in India. In your first year, success looks like an SSDL that scales with engineering rather than gating it, security review embedded in how new initiatives ship, and accurate, on-demand vulnerability reporting backed by a working path to resolution. What You'll Do Own and operate a scalable secure software development lifecycle: threat modeling, security requirements, secure design practices, and scanning that engineering can readily adopt. Partner with engineering on security features and secure-by-design architecture, from early design through i
Work Flexibility: Hybrid or Onsite **23 month fixed term contract** All benefits included Hybrid, Carrigtwohill, Cork Join Our Team as a Senior Engineer, Advanced Operations Are you an experienced and innovative engineering professional with a passion for advancing cutting-edge technologies in the medical field? We are looking for a proactive, results-driven Senior Engineer to support our NPI programs working on our Patient Specific Joint Replacement portfolio. In this role, you will develop solutions to technical challenges of moderate scope and complexity, while playing a key part in leveraging engineering techniques to ensure NPI launch excellence. You will also lead continuous improvement initiatives aimed at accelerating time to market, driving cost efficiencies, and expanding margins by implementing innovative additive technologies and processes that differentiate our products and give us a competitive edge in the market. Key Responsibilities: Innovative Technology Integration: Support the integration of cutting-edge additive manufacturing technologies for joint replacement products, optimizing efficiency and precision in accordance with Stryker's new product development and design transfer procedures. Relationship Building and Mentorship: Foster productive relationships both internally and externally, playing a pivotal role in team dynamics. Provide periodic guidance and training to team members, contributing to a culture of continuous learning and growth. Quality Assurance and Product Optimization: Oversee and ensure the quality of processes and products, aligning with operational standards and material specifications to deliver superior joint replacement pro
Location Details: India, Remote 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 Do you want to be an Information Security Lead at GoDaddy? GoDaddy’s Security organization is looking for a Cloud Security Engineer. We work out large-scale and cross-company security challenges while ensuring that partnership with the development and operational communities remains front of mind. At GoDaddy, Security Engineers apply their strong hands-on technical skills to craft scalable solutions for multiple problems. You must communicate with GoDaddy Engineering teams, perform security assessments, prioritize security risks, and design. We, as a team, implement high-quality security engineering solutions! What you'll get to do... The Senior Cloud Network Security Engineer will play a crucial role in designing, building, and securing large-scale, distributed cloud environments that support GoDaddy Services. This role operates at the intersection of cloud infrastructure, security architecture, and engineering execution. The successful candidate will collaborate closely with service teams, security leaders, and compliance partners to embed security-by-design principles into cloud services and internal platforms. This position requires advanced technical expertise in cloud-native security controls. It also needs a strong understanding of threat models in hyperscale environments. Additionally, it involves influencing architecture decisions across multiple teams. The role demands hands-on engineering, good judgment in ambiguous situations, and proficiency at translating security requirements into scalable, automated solutions. Bui
Senior Machine Learning Engineer Description - We are looking for a Senior MLOps Engineer to design, build, and operate the infrastructure that enables machine learning models and large language models to be deployed safely, reliably, and at scale. In this role, you will create the end-to-end capabilities required to move models from experimentation into production, expose them through secure and highly available endpoints, and enable users and applications to interact with AI-powered services. You will work across AWS and Databricks to establish robust CI/CD pipelines, model-serving infrastructure, observability, governance, rollback mechanisms, and operational standards. You will partner closely with data scientists, machine learning engineers, software engineers, security teams, and platform engineers. The ideal candidate combines strong cloud and DevOps engineering skills with a practical understanding of machine learning systems, LLM deployment patterns, and production reliability. Key Responsibilities MLOps Platform and Architecture Design and implement a scalable MLOps platform using AWS and Databricks. Define reference architectures and reusable deployment patterns for traditional machine learning models, deep learning models, and large language models. Build standardized workflows that move models from development and validation into staging and production. Develop self-service capabilities that allow data scientists and ML engineers to deploy models without manually managing infrastructure. Establish clear separation between development, testing, staging, and production environments. Design multi-region or multi-availability-zone architectures where required by business continuity and availability objectives. CI/CD and
Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Senior AI Platform Engineer (DevOps) Who is Mastercard? Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payment choices, making transactions secure, simple, smart, and accessible. Our technology and innovation, partnerships, and networks combined to deliver a unique set of products and services that help people, businesses, and governments realize their greatest potential. Our decency quotient (DQ) drives our culture and everything we do inside and outside our company. We cultivate an environment where individuals can thrive, collaborate, and contribute to innovations that power the global economy. Overview: The AI Platform Engineering team is responsible for building, operating, and evolving Mastercard's enterprise AI platforms and capabilities. Our mission is to provide scalable, secure, and reliable AI infrastructure that enables teams across Mastercard to accelerate the development and deployment of AI-powered solutions. As a Senior AI Engineer, you will help design, implement, and operate the foundational platforms that support AI and machine learning workloads across the enterprise. You will work at the intersect
Position summary: The Senior Security Engineer position will be part of the Enterprise Security organization consisting of IAM professionals across several technologies. This specific position will have a specialized role in directory services and SaaS applications! It will focus on large implementations of Entra ID with integrations with other directories, IDPs, applications, and automated workflows. We give technical direction, administer tools, and provide support for various security technologies. We participate in driving Enterprise Security projects that use our cloud directory services for various internal and external Adobe services. We work with other specialists, architects, security teams, and software engineer teams across Adobe and collectively provide services, guidance, and strategies that protect services and data as well as adhere to various global government regulations. You will work with business customers, management teams, infrastructure teams, development teams, project managers, and other security teams to help implement the vision, structure, standards, and plan solutions that support the future architecture. At Adobe, you will be immersed in an exceptional work environment that is recognized throughout the world on Best Companies lists! You will also be surrounded by colleagues who are committed to helping each other grow through our Check-In approach where ongoing feedback flows freely. If you’re looking to make an impact, Adobe is the place for you. Discover what our employees are saying about their career experiences on the Adobe Life blog and explore the meaningful benefits we offer. Adobe is an equal opportunity employer. We welcome and encourage diversity in the workplace regardless of race, gender, religion, age, sexual orientation, gender identity, disability or veteran status. Primary Responsibilities May Include, but Are Not Limited To: Managing deep an
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. We are seeking a Staff DB SRE to build the runtime foundation for NVIDIA’s enterprise AI platforms — with a strong emphasis on database infrastructure at scale. This role blends large-scale database transformation with the building and development of GPU-accelerated platforms. You'll develop the software systems, automation frameworks, and high-performance database services that power NVIDIA’s AI workloads at scale. What you'll be doing: Design and operate highly available database clusters (MySQL, MSSQL, Oracle) with automated replication, failover, point-in-time recovery, and disaster-recovery strategies at enterprise scale. Drive database performance engineering — own query optimization, indexing strategies, connection pooling, lock-contention analysis, and storage-engine tuning for production systems handling millions of transactions. Build self-service database lifecycle automation — from one-click cluster provisioning and schema migrations to zero-downtime upgrades, blue-green deployments, and automated capacity scaling. Bridge relational and AI-native data infrastructure — extend traditional database exper
The NVIDIA DGXC Data Services team builds cloud-native systems, frameworks, and services for managing data across hybrid and multi-cloud infrastructure. We are building the next-generation data and storage infrastructure to solve some of the hardest problems in AI: storage, access, ingestion, governance, observability, and data management for exabyte-scale, high-performance GPU-based training and inference jobs. Our work gives NVIDIA teams the foundational capabilities they need to build, train, deploy, and operate AI products at scale without reinventing critical data infrastructure for every workload. What you will be doing: Build cloud-native data and storage services for hybrid and multi-cloud infrastructure, including dataset discovery, ingestion, governance, checkpointing, observability, and low-latency access. Develop scalable cloud-native services and APIs that support exabyte-scale, high-performance GPU training and inference workflows. Work closely with product managers, internal AI teams, platform teams, and partner engineering teams to understand requirements and turn them into reliable production systems. Collaborate with SRE, operations, and support teams to improve service reliability, performance, observability, on-call readiness, and operational scale. Use modern software engineering practices, including AI-assisted and agentic development workflows, while maintaining high standards for design, testing, security, and verification. What we need to see: BS in Computer Science, Information Systems, Computer Engineering, or equivalent experience, with 5+ years of software engineering experience. Strong foundation in algorithms, data structures, distributed systems, and practi
The NVIDIA DGXC Data Services team builds cloud-native systems, frameworks, and services for managing data across hybrid and multi-cloud infrastructure. We are building the next-generation data and storage infrastructure to solve some of the hardest problems in AI: storage, access, ingestion, governance, observability, and data management for exabyte-scale, high-performance GPU-based training and inference jobs. Our work gives NVIDIA teams the foundational capabilities they need to build, train, deploy, and operate AI products at scale without reinventing critical data infrastructure for every workload. What you will be doing: Build storage technologies, client libraries, and filesystem frameworks that help AI workloads access data across object stores, file systems, and hybrid cloud infrastructure. Develop high-performance storage paths for training and inference workflows, including data loading, checkpointing, caching, POSIX-style access, and object-store integration. Build observability systems that diagnose storage bottlenecks, attribute GPU idle time to I/O behavior, and expose actionable telemetry through production monitoring stacks. Improve performance, scalability, and reliability of storage systems serving massive datasets, deep directory trees, and high-concurrency AI workloads. Work closely with internal AI teams, platform teams, SRE, and operations to validate storage behavior against real workloads and production environments. Use modern software engineering practices, including AI-assisted and agentic development workflows, while maintaining high standards for design, testing, security, performance, and verification. What we need to see: BS in Computer Science, Information Sys
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. We are the GPU Communications Libraries and Networking team at NVIDIA. We deliver libraries like NCCL, NVSHMEM, UCX for Deep Learning and HPC. We are looking for a motivated Performance engineer to influence the roadmap of our communication libraries. The DL and HPC applications of today have a huge compute demand and run on scales which go up to tens of thousands of GPUs. The GPUs are connected with high-speed interconnects (eg. NVLink, PCIe) within a node and with high-speed networking (eg. Infiniband, Ethernet) across the nodes. Communication performance between the GPUs has a direct impact on the end-to-end application performance; and the stakes are even higher at huge scales! This is an outstanding opportunity for someone with HPC and performance background to advance the state of the art in this space. Are you ready for to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Conduct in-depth performance characterization and analysis on large multi-GPU and multi-node clusters. Study the interaction of our libraries with all HW (GPU, CPU, Networking) and SW components in the stack Evaluate proof-of-concepts, conduct trade-off analysis when multiple solutions are available Triage and root-cause performance issues reported by our customers Collect a lot of performance data; build tools and infrastructure to visualize and analyze the information <li
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 an Assigned Support Engineer, you’ll be a trusted technical advisor to GitLab’s largest Self-managed, GitLab Dedicated, and GitLab.com customers, helping them avoid operational disruption and get the most from GitLab. You’ll combine deep Linux systems expertise, GitLab and CI/CD knowledge, and a proactive support mindset to understand each customer’s environment, anticipate and prevent issues, and solve complex technical and business challenges. In a typical week, you might be prioritizing strategic blockers with customer stakeholders, partnering with Product, Development, Infrastructure, Customer Succ
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 an Assigned Support Engineer, you’ll be a trusted technical advisor to GitLab’s largest Self-managed, GitLab Dedicated, and GitLab.com customers, helping them avoid operational disruption and get the most from GitLab. You’ll combine deep Linux systems expertise, GitLab and CI/CD knowledge, and a proactive support mindset to understand each customer’s environment, anticipate and prevent issues, and solve complex technical and business challenges. In a typical week, you might be prioritizing strategic blockers with customer stakeholders, partnering with Product, Development, Infrastructure, Customer Succ
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