As a Site Reliability Engineer, you balance the day-to-day operations on production systems with long-term software engineering improvements to reduce operational toil and foster the reliability, availability, and performance of these systems.

Key Responsibilities:

• Design, build, and maintain scalable, highly available and fault-tolerant infrastructures to support our web services and ML workloads
• Ensure our platform, inference and model training environments are always highly available and enable seamless replication of work environments across several HPC clusters
• Operate systems and troubleshoot issues in production environments (interrupts, on-call responses, users admin, data extraction, infrastructure scaling, etc.)
• Implement and improve monitoring, alerting, and incident response systems to ensure optimal system performance and minimize downtime
• Implement and maintain workflows and tools (CI/CD, containerization, orchestration, monitoring, logging and alerting systems) for both our client-facing APIs and large training runs

Development Responsibilities:

• Drive continuous improvement in infrastructure automation, deployment, and orchestration using tools like Kubernetes, Flux, Terraform
• Collaborate with AI/ML researchers to develop and implement solutions that enable safe and reproducible model-training experiments
• Build a cloud-agnostic platform offering an abstraction layer between science and infrastructure
• Design and develop new workflows and tooling to improve to the reliability, availability and performance of our systems (automation scripts, refactoring, new API-based features, web apps, dashboards, etc.)
• Collaborate with the security team to ensure infrastructure adheres to best security practices and compliance requirements
• Document processes and procedures to ensure consistency and knowledge sharing across the team
• Contribute to open-source projects, research publications, blog articles and conferences

Requirements:

• Master’s degree in Computer Science, Engineering or a related field
• 7+ years of experience in a DevOps/SRE role
• Strong experience with cloud computing and highly available distributed systems
• Exposure to site reliability issues in critical environments (issue root cause analysis, in-production troubleshooting, on-call rotations...)
• Experience working against reliability KPIs (observability, alerting, SLAs)
• Hands-on experience with CI/CD, containerization and orchestration tools (Docker, Kubernetes...)
• Knowledge of monitoring, logging, alerting and observability tools (Prometheus, Grafana, ELK Stack, Datadog...)
• Familiarity with infrastructure-as-code tools like Terraform or CloudFormation
• Proficiency in scripting languages (Python, Go, Bash...) and knowledge of software development best practices
• Strong understanding of networking, security, and system administration concepts
• Excellent problem-solving and communication skills

Preferred Qualifications:

• Experience in an AI/ML environment
• Experience of high-performance computing (HPC) systems and workload managers (Slurm)
• Worked with modern AI-oriented solutions (Fluidstack, Coreweave, Vast...)

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Your key responsibilities will include designing, building, and maintaining scalable, highly available, and fault-tolerant infrastructures; operating systems and troubleshooting issues in production environments; implementing and improving monitoring, alerting, and incident response systems; and participating in on-call rotations to respond to incidents and perform root cause analysis.

In addition, you will drive continuous improvement in infrastructure automation, deployment, and orchestration; collaborate with software engineers to develop and implement solutions that enable safe and reproducible model-training experiments; help build a cloud platform offering an abstraction layer between science, engineering, and infrastructure; and design and develop new workflows and tooling to improve the reliability, availability, and performance of our systems.

To be successful in this role, you will need a Master's degree in Computer Science, Engineering, or a related field, and 5+ years of experience in a DevOps/SRE role. You should have strong experience with bare metal infrastructure and highly available distributed systems, exposure to site reliability issues in critical environments, and experience working against reliability KPIs (observability, alerting, SLAs).

You should also be hands-on with CI/CD, containerization, and orchestration tools (Docker, Kubernetes); knowledgeable about monitoring, logging, alerting, and observability tools (Prometheus, Grafana, ELK Stack, Datadog); familiar with infrastructure-as-code tools like Terraform or CloudFormation; proficient in scripting languages (Python, Go, Bash); and have a strong understanding of networking, security, and system administration concepts.

Experience in an AI/ML environment, high-performance computing (HPC) systems, and workload managers (Slurm) is a plus.

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As a Site Reliability Engineer, you balance the day-to-day operations on production systems with long-term software engineering improvements to reduce operational toil and foster the reliability, availability, and performance of these systems.

Responsibilities

• Design, build, and maintain scalable, highly available and fault-tolerant infrastructures to support our web services and ML workloads
• Make sure our platform, inference and model training environments are always highly available and enable seamless replication of work environments across several HPC clusters
• Operate systems and troubleshoot issues in production environments (interrupts, on-call responses, users admin, data extraction, infrastructure scaling, etc.)
• Implement and improve monitoring, alerting, and incident response systems to ensure optimal system performance and minimize downtime
• Implement and maintain workflows and tools (CI/CD, containerization, orchestration, monitoring, logging and alerting systems) for both our client-facing APIs and large training runs
• Participate occasionally in on-call rotations to respond to incidents and perform root cause analysis to prevent future occurrences

Development

• Drive continuous improvement in infrastructure automation, deployment, and orchestration using tools like Kubernetes, Flux, Terraform
• Collaborate with AI/ML researchers to develop and implement solutions that enable safe and reproducible model-training experiments
• Build a cloud-agnostic platform offering an abstraction layer between science and infrastructure
• Design and develop new workflows and tooling to improve to the reliability, availability and performance of our systems (automation scripts, refactoring, new API-based features, web apps, dashboards, etc.)
• Collaborate with the security team to ensure infrastructure adheres to best security practices and compliance requirements
• Document processes and procedures to ensure consistency and knowledge sharing across the team
• Contribute to open-source projects, research publications, blog articles and conferences

Requirements

• Master’s degree in Computer Science, Engineering or a related field
• 7+ years of experience in a DevOps/SRE role
• Strong experience with cloud computing and highly available distributed systems
• Exposure to site reliability issues in critical environments (issue root cause analysis, in-production troubleshooting, on-call rotations...)
• Experience working against reliability KPIs (observability, alerting, SLAs)
• Hands-on experience with CI/CD, containerization and orchestration tools (Docker, Kubernetes...)
• Knowledge of monitoring, logging, alerting and observability tools (Prometheus, Grafana, ELK Stack, Datadog...)
• Familiarity with infrastructure-as-code tools like Terraform or CloudFormation
• Proficiency in scripting languages (Python, Go, Bash...) and knowledge of software development best practices
• Strong understanding of networking, security, and system administration concepts
• Excellent problem-solving and communication skills

Nice to Have

• Experience in an AI/ML environment
• Experience of high-performance computing (HPC) systems and workload managers (Slurm)
• Worked with modern AI-oriented solutions (Fluidstack, Coreweave, Vast...)

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You will work closely with our software engineers and product teams to ensure our systems meet and exceed our internal and external customers' expectations.

Key responsibilities include:

• Design, build, and maintain scalable, highly available and fault-tolerant infrastructures
• Operate systems and troubleshoot issues in production environments
• Implement and improve monitoring, alerting, and incident response systems
• Implement and maintain workflows and tools for both our customer-facing APIs and large training runs

Development responsibilities include:

• Drive continuous improvement in infrastructure automation, deployment, and orchestration
• Collaborate with software engineers to develop and implement solutions that enable safe and reproducible model-training experiments
• Help build a cloud platform offering an abstraction layer between science, engineering and infrastructure
• Design and develop new workflows and tooling to improve the reliability, availability and performance of our systems

Additional responsibilities include:

• Collaborate with the security team to ensure infrastructure adheres to best security practices and compliance requirements
• Document processes and procedures to ensure consistency and knowledge sharing across the team
• Contribute to open-source projects, research publications, blog articles and conferences

About you:

• Master’s degree in Computer Science, Engineering or a related field
• 5+ years of experience in a DevOps/SRE role
• Strong experience with bare metal infrastructure and highly available distributed systems
• Exposure to site reliability issues in critical environments
• Experience working against reliability KPIs
• Hands-on experience with CI/CD, containerization and orchestration tools
• Knowledge of monitoring, logging, alerting and observability tools
• Familiarity with infrastructure-as-code tools
• Proficiency in scripting languages and knowledge of software development best practices
• Strong understanding of networking, security, and system administration concepts
• Excellent problem-solving and communication skills

Your application will be all the more interesting if you also have:

• Experience in an AI/ML environment
• Experience of high-performance computing (HPC) systems and workload managers
• Worked with modern AI-oriented solutions

XML job scraping automation by YubHub

At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.

We are a dynamic team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation.

Role Summary

We are seeking highly experienced Site Reliability Engineers (SRE) to shape the reliability, scalability and performance of our platform and customer facing applications. You will work closely with our software engineers and research teams to ensure our systems meet and exceed our internal and external customers' expectations.

Responsibilities

As a Site Reliability Engineer, you balance the day-to-day operations on production systems with long-term software engineering improvements to reduce operational toil and foster the reliability, availability, and performance of these systems.

Operations

• Design, build, and maintain scalable, highly available and fault-tolerant infrastructures to support our web services and ML workloads

• Make sure our platform, inference and model training environments are always highly available and enable seamless replication of work environments across several HPC clusters

• Operate systems and troubleshoot issues in production environments (interrupts, on-call responses, users admin, data extraction, infrastructure scaling, etc.)

• Implement and improve monitoring, alerting, and incident response systems to ensure optimal system performance and minimize downtime

• Implement and maintain workflows and tools (CI/CD, containerization, orchestration, monitoring, logging and alerting systems) for both our client-facing APIs and large training runs

• Participate occasionally in on-call rotations to respond to incidents and perform root cause analysis to prevent future occurrences

Development

• Drive continuous improvement in infrastructure automation, deployment, and orchestration using tools like Kubernetes, Flux, Terraform

• Collaborate with AI/ML researchers to develop and implement solutions that enable safe and reproducible model-training experiments

• Build a cloud-agnostic platform offering an abstraction layer between science and infrastructure

• Design and develop new workflows and tooling to improve to the reliability, availability and performance of our systems (automation scripts, refactoring, new API-based features, web apps, dashboards, etc.)

• Collaborate with the security team to ensure infrastructure adheres to best security practices and compliance requirements

• Document processes and procedures to ensure consistency and knowledge sharing across the team

• Contribute to open-source projects, research publications, blog articles and conferences

About You

• Master’s degree in Computer Science, Engineering or a related field

• 7+ years of experience in a DevOps/SRE role

• Strong experience with cloud computing and highly available distributed systems

• Exposure to site reliability issues in critical environments (issue root cause analysis, in-production troubleshooting, on-call rotations...)

• Experience working against reliability KPIs (observability, alerting, SLAs)

• Hands-on experience with CI/CD, containerization and orchestration tools (Docker, Kubernetes...)

• Knowledge of monitoring, logging, alerting and observability tools (Prometheus, Grafana, ELK Stack, Datadog...)

• Familiarity with infrastructure-as-code tools like Terraform or CloudFormation

• Proficiency in scripting languages (Python, Go, Bash...) and knowledge of software development best practices

• Strong understanding of networking, security, and system administration concepts

• Excellent problem-solving and communication skills

• Self-motivated and able to work well in a fast-paced startup environment

Your Application Will Be All The More Interesting If You Also Have:

• Experience in an AI/ML environment

• Experience of high-performance computing (HPC) systems and workload managers (Slurm)

• Worked with modern AI-oriented solutions (Fluidstack, Coreweave, Vast...)

XML job scraping automation by YubHub

At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments.

Role Summary

We are seeking highly experienced Site Reliability Engineers (SRE) to shape the reliability, scalability and performance of our platform and customer facing applications. You will work closely with our software engineers and research teams to ensure our systems meet and exceed our internal and external customers' expectations.

Responsibilities

As a Site Reliability Engineer, you balance the day-to-day operations on production systems with long-term software engineering improvements to reduce operational toil and foster the reliability, availability, and performance of these systems.

Operations (50%)

• Design, build, and maintain scalable, highly available and fault-tolerant infrastructures to support our web services and ML workloads
• Make sure our platform, inference and model training environments are always highly available and enable seamless replication of work environments across several HPC clusters
• Operate systems and troubleshoot issues in production environments (interrupts, on-call responses, users admin, data extraction, infrastructure scaling, etc.)
• Implement and improve monitoring, alerting, and incident response systems to ensure optimal system performance and minimize downtime
• Implement and maintain workflows and tools (CI/CD, containerization, orchestration, monitoring, logging and alerting systems) for both our client-facing APIs and large training runs
• Participate occasionally in on-call rotations to respond to incidents and perform root cause analysis to prevent future occurrences

Development (50%)

• Drive continuous improvement in infrastructure automation, deployment, and orchestration using tools like Kubernetes, Flux, Terraform
• Collaborate with AI/ML researchers to develop and implement solutions that enable safe and reproducible model-training experiments
• Build a cloud-agnostic platform offering an abstraction layer between science and infrastructure
• Design and develop new workflows and tooling to improve to the reliability, availability and performance of our systems (automation scripts, refactoring, new API-based features, web apps, dashboards, etc.)
• Collaborate with the security team to ensure infrastructure adheres to best security practices and compliance requirements
• Document processes and procedures to ensure consistency and knowledge sharing across the team
• Contribute to open-source projects, research publications, blog articles and conferences

About You

• Master’s degree in Computer Science, Engineering or a related field
• 7+ years of experience in a DevOps/SRE role
• Strong experience with cloud computing and highly available distributed systems
• Exposure to site reliability issues in critical environments (issue root cause analysis, in-production troubleshooting, on-call rotations...)
• Experience working against reliability KPIs (observability, alerting, SLAs)
• Hands-on experience with CI/CD, containerization and orchestration tools (Docker, Kubernetes...)
• Knowledge of monitoring, logging, alerting and observability tools (Prometheus, Grafana, ELK Stack, Datadog...)
• Familiarity with infrastructure-as-code tools like Terraform or CloudFormation
• Proficiency in scripting languages (Python, Go, Bash...) and knowledge of software development best practices
• Strong understanding of networking, security, and system administration concepts
• Excellent problem-solving and communication skills
• Self-motivated and able to work well in a fast-paced startup environment

Your Application Will Be All The More Interesting If You Also Have:

• Experience in an AI/ML environment
• Experience of high-performance computing (HPC) systems and workload managers (Slurm)
• Worked with modern AI-oriented solutions (Fluidstack, Coreweave, Vast...)

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