About Graphcore
How often do you get the chance to build a technology that transforms the future of humanity? Graphcore products have set the standard in made-for-AI compute hardware and software, gaining global attention and industry acclaim. Now we are developing the next generation of artificial intelligence compute with systems that will allow AI researchers to develop more advanced models, help scientists unlock exciting new discoveries, and power companies around the world as they put AI at the heart of their business. Graphcore recently joined SoftBank Group – bringing large and ongoing investment from one of the world’s leading backers of innovative AI companies.
Job Summary
As a
Cloud Software Engineer , you will play a critical role in enabling new AI accelerator hardware within Kubernetes environments. This position focuses on investigating how to integrate the new generation of our hardware into key MLOps technologies from the Kubernetes ecosystem, such as
Kubeflow ,
Volcano ,
Kueue , and others. Additionally, you will be responsible for
developing Go applications , ensuring a seamless and native Kubernetes end-user experience. While Kubernetes integration is the primary responsibility, this role emphasizes the importance of
MLOps
and
machine learning (ML) knowledge
to effectively support the development of K8s integration.
Please be aware that this is not a DevOps position; read on for further details on the role requirements. Responsibilities and Duties Investigate integration strategies for our AI accelerator hardware with MLOps technologies in the Kubernetes ecosystem, such as
Kubeflow ,
Volcano ,
Kueue , and others. Develop and maintain
applications in Go
for integrating new AI accelerator hardware into Kubernetes environments. Ensure
seamless hardware integration
with Kubernetes clusters, delivering a native end-user experience. Participate in code reviews, design discussions, and troubleshooting sessions to enhance system reliability and performance. Maintain high software quality standards by following best practices. Write and maintain comprehensive documentation for code, projects, and integration guides. Stay up-to-date with the latest trends in Kubernetes, AI/ML technologies, and MLOps workflows to ensure the platform remains cutting-edge. Skills and Experience Essential Qualifications Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience. At least 3 years of experience in
software development . Experience with
machine learning technologies
in the Kubernetes ecosystem, such as
Kubeflow ,
Volcano , and
Kueue . Familiarity with
MLOps workflows and tools
for deploying and managing machine learning workloads. Working knowledge of
Go
or Python programming language. Expertise in
Kubernetes , including resource management and scaling. Familiarity with
Linux . English proficiency at a
B2 level . Preferred Qualifications Knowledge of
distributed training frameworks
and techniques for scaling machine learning workloads. Hands-on experience with cloud platforms such as AWS, Azure, or GCP, including their machine learning services. Knowledge of container orchestration and cloud-native development. Familiarity with CI/CD pipelines and DevOps tools like GitHub or GitLab. Benefits
In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments. Sponsorship Applicants for this position must hold the right to work in the UK. Unfortunately, at this time, we are unable to provide visa sponsorship or support for visa applications.
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Cloud Software Engineer , you will play a critical role in enabling new AI accelerator hardware within Kubernetes environments. This position focuses on investigating how to integrate the new generation of our hardware into key MLOps technologies from the Kubernetes ecosystem, such as
Kubeflow ,
Volcano ,
Kueue , and others. Additionally, you will be responsible for
developing Go applications , ensuring a seamless and native Kubernetes end-user experience. While Kubernetes integration is the primary responsibility, this role emphasizes the importance of
MLOps
and
machine learning (ML) knowledge
to effectively support the development of K8s integration.
Please be aware that this is not a DevOps position; read on for further details on the role requirements. Responsibilities and Duties Investigate integration strategies for our AI accelerator hardware with MLOps technologies in the Kubernetes ecosystem, such as
Kubeflow ,
Volcano ,
Kueue , and others. Develop and maintain
applications in Go
for integrating new AI accelerator hardware into Kubernetes environments. Ensure
seamless hardware integration
with Kubernetes clusters, delivering a native end-user experience. Participate in code reviews, design discussions, and troubleshooting sessions to enhance system reliability and performance. Maintain high software quality standards by following best practices. Write and maintain comprehensive documentation for code, projects, and integration guides. Stay up-to-date with the latest trends in Kubernetes, AI/ML technologies, and MLOps workflows to ensure the platform remains cutting-edge. Skills and Experience Essential Qualifications Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience. At least 3 years of experience in
software development . Experience with
machine learning technologies
in the Kubernetes ecosystem, such as
Kubeflow ,
Volcano , and
Kueue . Familiarity with
MLOps workflows and tools
for deploying and managing machine learning workloads. Working knowledge of
Go
or Python programming language. Expertise in
Kubernetes , including resource management and scaling. Familiarity with
Linux . English proficiency at a
B2 level . Preferred Qualifications Knowledge of
distributed training frameworks
and techniques for scaling machine learning workloads. Hands-on experience with cloud platforms such as AWS, Azure, or GCP, including their machine learning services. Knowledge of container orchestration and cloud-native development. Familiarity with CI/CD pipelines and DevOps tools like GitHub or GitLab. Benefits
In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments. Sponsorship Applicants for this position must hold the right to work in the UK. Unfortunately, at this time, we are unable to provide visa sponsorship or support for visa applications.
#J-18808-Ljbffr
