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, networking, load balancing (including our public-facing edge and internal service mesh), and observability and alerting systems. The Deployments team designs and maintains our continuous delivery infrastructure, ensuring reliable code deployment from development through production for all engineering teams. This infrastructure is primarily composed of Argo Workflows and ArgoCD. The team also provides tooling that enables clear system ownership and facilitates self-service onboarding for development teams. We are looking to speak to candidates who can work East Coast hours. The ideal candidate should Have 6+ years of experience in software development and operating distributed systems Proficiency in Python, Go, or a similar language Proven experience building and operating large-scale continuous integration and continuous deployment (CI/CD) pipelines Possess a customer-focused mindset Value efficiency in processes and operations Prefer automation over manual process (“allergic to ops work”). We are a small team of software engineers with a strong bias towards software solutions to avoid toil Experience using and extending containerization technologies, particularly Kubernetes, to enhance application agility, optimize resource utilization, and accelerate time-to-market Expertise in cloud infrastructure platforms, including AWS, Google Cloud Platform (GCP), or Azure Understanding of Linux operating system internals and networking concepts (e.g., TCP/IP, DNS, TLS, routing) Expectations Contribute to developing a world-class continuous deployment experience, enabling the rapid and reliable shipment of MongoDB products This includes, but is not limited to, contributing to open-source projects, or engineering software-based
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The Team This role can sit in our NYC HQ on a hybrid basis, or it can be fully remote while working from a location based in either Eastern or Central time zones. We are looking for an experienced Senior Engineer for our SRE, Atlas team to support, maintain and grow the Atlas platform. As a senior SRE, you will be expected to be able to design & build complex systems, operate with autonomy and act as owner for everything you do. The SRE Atlas team works alongside the various Atlas software engineering teams to provide expertise about running systems at scale, build new tooling and automation and perform essential maintenance of the Atlas fleet. This is an SRE team, which means you can expect a highly hands-on approach, tackling the technical challenges of implementing large scale solutions that have the ability to impact our customer’s most crucial workloads. Role Overview We are seeking a talented Site Reliability Engineer (SRE) with a strong infrastructure background. This role requires engineers to have a customer-first mindset to ensure that everything we do results in a stronger product and a better experience for all Atlas customers. The ideal candidate should Have 5+ years of experience running critical systems at scale Value efficiency in processes and operations, and display a preference for automation over manual processes (“allergic to ops work”) Be familiar with a major cloud provider (AWS, Azure, or GCP) and possess the ability to build and operate systems in a multi-cloud environment A strong understanding of how to run a large scale Linux environment, including low level fundamentals Firm grasp of at least one modern programming language, beyond basic scripting (Go, Ruby, Python) Solid understanding of web and network protocols and standards (HTTP, TLS, DNS, etc) Special Requirements: Be a US Citizen Expectations Participate in the development of a reliable and resilient multi-cloud platform that hosts business critic
Senior: GBP 73,500 - 99,500 Staff: GBP 97,300 - 131,700 Subject to alignment to the responsibilities and duties of the role - we currently have multiple positions available at both Senior and Staff level. About the job Build the Linux distribution foundation that turns upstream software into trusted Graphcore platform releases. You will help create the Linux distribution that powers Graphcore AI systems. The team produces production-ready system images from proven upstream distributions. Your work will shape how releases are built, validated and prepared for deployment. You will strengthen the engineering path from upstream Linux software to dependable platform releases. You will build and improve automated pipelines, run established Linux test suites, and diagnose issues across build and validation flows. As the platform evolves, you will introduce controlled configuration and tuning changes with evidence-led validation. This is hands-on systems engineering with visible impact. You will help define reliable processes for a new team building a critical part of Graphcore’s platform. The team and culture You will join one of Graphcore’s newest engineering teams, helping shape its culture from the start. It is a small, co-located team where ownership matters and progress is visible. Work happens through close technical discussion, practical problem-solving and evidence-led decisions. Ideas are challenged openly, and the best path wins regardless of hierarchy. You will report to a leader who values technical credibility and invests in people’s growth. The team moves with pace, takes responsibility and changes direction when the evidence demands it. What we're looking for Strong practical experience working in Linux environments Experience building or maintaining automated CI/CD pipelines for reliable engineering workflows Proficiency in Python, Bash or similar
Senior: GBP 73,500 - 99,500 Staff: GBP 97,300 - 131,700 Subject to alignment to the responsibilities and duties of the role - we currently have multiple positions available at both Senior and Staff level. About the job Build the Linux distribution foundation that turns upstream software into trusted Graphcore platform releases. You will help create the Linux distribution that powers Graphcore AI systems. The team produces production-ready system images from proven upstream distributions. Your work will shape how releases are built, validated and prepared for deployment. You will strengthen the engineering path from upstream Linux software to dependable platform releases. You will build and improve automated pipelines, run established Linux test suites, and diagnose issues across build and validation flows. As the platform evolves, you will introduce controlled configuration and tuning changes with evidence-led validation. This is hands-on systems engineering with visible impact. You will help define reliable processes for a new team building a critical part of Graphcore’s platform. The team and culture You will join one of Graphcore’s newest engineering teams, helping shape its culture from the start. It is a small, co-located team where ownership matters and progress is visible. Work happens through close technical discussion, practical problem-solving and evidence-led decisions. Ideas are challenged openly, and the best path wins regardless of hierarchy. You will report to a leader who values technical credibility and invests in people’s growth. The team moves with pace, takes responsibility and changes direction when the evidence demands it. What we're looking for Strong practical experience working in Linux environments Experience building or maintaining automated CI/CD pipelines for reliable engineering workflows Proficiency in Python, Bash or similar
Senior: GBP 73,500 - 99,500 Staff: GBP 97,300 - 131,700 Subject to alignment to the responsibilities and duties of the role - we currently have multiple positions available at both Senior and Staff level. About the job Build the Linux distribution foundation that turns upstream software into trusted Graphcore platform releases. You will help create the Linux distribution that powers Graphcore AI systems. The team produces production-ready system images from proven upstream distributions. Your work will shape how releases are built, validated and prepared for deployment. You will strengthen the engineering path from upstream Linux software to dependable platform releases. You will build and improve automated pipelines, run established Linux test suites, and diagnose issues across build and validation flows. As the platform evolves, you will introduce controlled configuration and tuning changes with evidence-led validation. This is hands-on systems engineering with visible impact. You will help define reliable processes for a new team building a critical part of Graphcore’s platform. The team and culture You will join one of Graphcore’s newest engineering teams, helping shape its culture from the start. It is a small, co-located team where ownership matters and progress is visible. Work happens through close technical discussion, practical problem-solving and evidence-led decisions. Ideas are challenged openly, and the best path wins regardless of hierarchy. You will report to a leader who values technical credibility and invests in people’s growth. The team moves with pace, takes responsibility and changes direction when the evidence demands it. What we're looking for Strong practical experience working in Linux environments Experience building or maintaining automated CI/CD pipelines for reliable engineering workflows Proficiency in Python, Bash or similar
Senior: PLN 260,400 - 352,200 Staff: PLN 350,700 - 474,400 Subject to alignment to the responsibilities and duties of the role - we currently have multiple positions available at both Senior and Staff level. About the job Build the Linux distribution foundation that turns upstream software into trusted Graphcore platform releases. You will help create the Linux distribution that powers Graphcore AI systems. The team produces production-ready system images from proven upstream distributions. Your work will shape how releases are built, validated and prepared for deployment. You will strengthen the engineering path from upstream Linux software to dependable platform releases. You will build and improve automated pipelines, run established Linux test suites, and diagnose issues across build and validation flows. As the platform evolves, you will introduce controlled configuration and tuning changes with evidence-led validation. This is hands-on systems engineering with visible impact. You will help define reliable processes for a new team building a critical part of Graphcore’s platform. The team and culture You will join one of Graphcore’s newest engineering teams, helping shape its culture from the start. It is a small, co-located team where ownership matters and progress is visible. Work happens through close technical discussion, practical problem-solving and evidence-led decisions. Ideas are challenged openly, and the best path wins regardless of hierarchy. You will report to a leader who values technical credibility and invests in people’s growth. The team moves with pace, takes responsibility and changes direction when the evidence demands it. What we're looking for Strong practical experience working in Linux environments Experience building or maintaining automated CI/CD pipelines for reliable engineering workflows Proficiency in Python, Bash or simil
Senior: PLN 260,400 - 352,200 Staff: PLN 350,700 - 474,400 Subject to alignment to the responsibilities and duties of the role - we currently have multiple positions available at both Senior and Staff level About Graphcore At Graphcore, we’re building the future of AI compute. We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale. As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem. To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world. We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence Job Summary As a Senior Machine Learning Engineer in the Applied AI team at Graphcore, you will contribute to advancing AI technology by developing and optimising AI models tailored to our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Working closely with the Software development and Research teams, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. We seek engineers with strong technical skills and an understanding of AI model implementation at scale, eager to make a tangible impact in this rapidly evolving field. The Team The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. We build reference applications, contribute to key software libraries e.g. optimising kernels for efficiency on our hardware, and collaborate with the Research team to develop
Senior: PLN 260,400 - 352,200 Staff PLN 350,700 - 474,400 Subject to alignment to the responsibilities and duties of the role - we currently have multiple positions available at both Senior and Staff level. About the job Build the quality foundations for Kubernetes systems that power next-generation AI compute. As a Staff QA Engineer, you will validate the workload management stack for new AI accelerator hardware. You will help ensure our Kubernetes integrations are robust, scalable and ready for production. Your work will shape how accelerators are scheduled, orchestrated and used across distributed environments. You will test the systems that make complex AI compute infrastructure reliable for real users. You will design automated test suites, build system and integration tests, and improve CI/CD quality practices. You will also debug issues across Kubernetes, infrastructure and applications. This role is for someone who wants to raise engineering quality across a deeply technical platform. The team and culture You will join the Workload Management team, working closely with software engineers and infrastructure specialists. The work is hands-on, systems-focused and driven by clear technical ownership. Quality is built early here, not checked at the end. You will influence test strategy, validation plans and automation practices across the development lifecycle. The team moves through open technical discussion and evidence-based decisions. You will mentor others, speak up on risk and help turn complex systems into dependable products. What we’re looking for Strong Python programming experience, with a focus on automation and test engineering Hands-on experience with Robot Framework or similar automation frameworks Experience testing cloud-native, containerised or distributed systems Strong Linux understanding and confidence debugging across multiple system layers Experience with CI/CD systems such as GitLab CI or GitHub Actions Ability to define quality standards,
Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries. JOB DESCRIPTION: A senior engineering professional who independently applies advanced knowledge to complete complex assignments, who leads the design and development of complex software code, unit tests and integration tests for a subsystem. MAIN RESPONSIBILITIES • Leads, is accountable for, and serves as the technical subject matter expert for the engineering design and implementation for one or more software features, identifying process issues and recommending corrective measures. • Defines feature evolution, branching, integration and deployment strategy. • Defines structure of the source code files. • Ensures successful integration. • Implements hardware/interface simulation. • Analyzes user needs, product requirements, software requirements and provides input to stakeholders Education Level Major/Field of Study or Equivalent: Bachelors Degree (± 16 years) Experience/Background Minimum 6 years Minimum 6 - 12 Years of experience The base pay for this position is $99,300.00 – $198,700.00 In specific locations, the pay range may vary from the range posted. JOB FAMILY: Product Development DIVISION: ONCO Cancer Diagnostics LOCATION:<
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. About the role: Join our Site Reliability Engineering (SRE) team and help ensure the reliability, scalability, and performance of Replit's infrastructure that serves millions of developers worldwide. As a Staff Site Reliability Engineer, you will bridge the gap between development and operations, implementing automation and establishing best practices that enable our platform to scale efficiently while maintaining high availability. We are seeking Staff SREs who are passionate about building and maintaining resilient systems at scale. Your mission will be to proactively find and analyze reliability problems across our stack, then design and implement software and systems to create step-function improvements. You will design robust observability solutions, lead incident response, automate operational tasks, and continuously improve our infrastructure's reliability, all while mentoring and educating the broader engineering team to make reliability a core value at Replit. You Will: Architect and Implement Observability: Design, build, and lead the implementation of comprehensive monitoring, logging, and tracing solutions. Create dashboards and metrics that provide real-time visibility into system health and performance, enabling proactive issue detection. Define and Drive Reliability Standards: Work with product and engineering teams to define, implement, and track Service Level Objectives (SLOs) and Service Level Indicators (SLIs). Build systems to monitor and report on these metrics, holding teams accountable and ensuring we maintain high reliability standards while balancing innovation speed. Lead Incident Management and Response: Act as a senior leader during high-impact incidents, guiding the team to rapid resolution
Salary Range: (Determined during interview process, based on technical fit for each level of role) Staff Engineer - PLN 350,700 - 474,400 + Benefits + Equity Senior Engineer - PLN 260,400 - 352,200 + Benefits + Equity Subject to alignment to the responsibilities and duties of the role. Location: Gdańsk - Hybrid Working Policy - 3 Days per week in office About the job Explore how a next-generation AI architecture behaves from rack scale to data centre scale. As a Senior Systems Engineer, you will investigate a novel AI computing architecture under demanding real-world workloads. You will turn complex system behaviour into measurable evidence. You will design experiments, benchmark representative AI workloads and explore how hardware components and software interact at scale. When behaviour is unexpected, you will turn uncertainty into new measurements. Your work will help infrastructure engineers, architects and application specialists understand performance, scalability and reliability across the stack. You will also help develop tooling and automation to collect, analyse and visualise system metrics. You do not need to be an AI expert. You will need strong judgement, a clear preference for evidence over opinion and a desire to explore complex systems beyond the obvious. The team and culture The System QA team is distributed across multiple locations so we work deliberately to stay connected. Daily team meetings create space to share ideas, ask questions, discuss findings and solve problems together. You will have regular 1:1s with your people manager where you will have the opportunity to discuss things that matter to you. You will have dedicated time each week to focus on your CPD. The technical lead will provide direction and help set priorities, but everyone in the team is there to support each other. Decisions are guided by evidence, clear communication and a willingness to challenge assumptions. Your manager will trust you to follow the evidence w
About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.
About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.
About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.
Location: Bristol, London or Cambridge, UK About the job Help scale state-of-the art AI models across thousands of accelerators. As a Senior Machine Learning Engineer in the Applied AI team, you will contribute to advancing AI technology by developing and optimising new and existing AI models for our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Having visibility of the entire pipeline from novel accelerator hardware to state-of-the-art AI applications, and the software stack in-between, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. Furthermore, you’ll work closely with researchers in a rapidly-evolving field, where even the most senior engineers are constantly learning and adapting to exciting new challenges. We seek engineers with strong technical foundations who are curious and eager to understand and advance AI model implementation, at scale. We currently have multiple opportunities available in the team at Senior, Staff and Principal level and offer flexibility through a hybrid working model, from any of our UK offices. If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you! The team and culture The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software, as well as our own hardware and software stack, to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. Our work spans from low-level kernel development and optimisation for novel hardware through to implementing and scaling research-level algorithms for the latest AI models. We collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and di
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