This role focuses on rapidly developing new features, and working across partner teams to deliver solutions, and maximize impact for Google and top customers.

You will be instrumental in translating cutting-edge AI research into real-world products, and demonstrating the capabilities of latest-generation models.

We are looking for engineers with a strong track record of building and shipping AI-powered software, ideally with experience in early-stage environments where they have contributed to scaling products from initial concept to production.

The ideal candidate will be motivated by the opportunity to drive product & business impact.

Key responsibilities:

• Harness frontier models to drive real-world high-impact outcomes

• Build evaluations, training data, and infrastructure to support AI deployments and rapid iterations

• Collaborate with researchers and product managers to translate research advancements into tangible product features.

• Contribute to the development of best practices for building and deploying generative AI applications.

• Contribute signal to influence the development of frontier models

• Lead the architecture and development of new products & features from 0 to 1.

About you:

In order to set you up for success as a Staff Research Engineer, Applied AI at Google DeepMind, we look for the following skills and experience:

Required Skills:

• Bachelor's degree or equivalent practical experience.

• 8 years of experience in software development, and with data structures/algorithms.

• 5 years of hands-on experience in AI research (e.g. RL, finetuning, evals), AI applications, or model deployment

• Proven experience in rapidly developing and shipping software products.

• Deep understanding of software development best practices, including testing & deployment.

• Experience with cloud computing platforms and infrastructure (e.g., Google Cloud Platform, AWS, Azure).

• Substantial experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Hugging Face, etc.

• Ability to work in a fast-paced environment and adapt to changing priorities.

Preferred Skills:

• Experience with generative AI research or applications.

• Contributions to open-source projects.

• Experience working in, or founding early stage startups.

• Experience delivering software solutions in a fast-paced, customer-facing environment.

If you are a passionate machine learning engineer with a drive to build innovative products and a desire to work at the forefront of AI, we encourage you to apply!

The US base salary range for this full-time position is between $197,000 - $291,000 + bonus + equity + benefits.

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Key responsibilities include:

• Architect scalable pipelines to unify disparate metrics into a single, accurate source of truth
• Enable advanced analytics through real-time and near-real-time dashboards for operational capacity and demand managers
• Support AI agent development by ensuring data pipelines are architected to synthesize complex data and inform high-stakes infrastructure decisions
• Cross-functional synthesis with Data Center Operations, Supply Chain, Product, and Finance to ensure technical pipelines accurately reflect the physical realities of data center bring-up and node health

The ideal candidate will have a Master's or PhD in Computer Science, Computer Engineering, Operations Research, or a related quantitative field, with 6+ years of professional experience in data engineering or data science. They will have expert-level proficiency in Python and SQL, and experience with modern data stack tools and software development best practices.

In addition to a competitive salary, CoreWeave offers a variety of benefits, including medical, dental, and vision insurance, company-paid life insurance, voluntary supplemental life insurance, short and long-term disability insurance, flexible spending account, health savings account, tuition reimbursement, employee stock purchase program, mental wellness benefits, family-forming support, paid parental leave, flexible PTO, catered lunch, and a casual work environment.

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Your primary focus will be on building and managing large-scale platforms to improve the availability of our Payments platform for internal and external stakeholders. You will collaborate closely with other Payments engineering teams and Infra teams to ensure services are instrumented, scalable, and resilient to support our growing business.

Key responsibilities include:

• Designing, implementing, and maintaining systems and tools at a platform level that support flow-level observability, payments reliability, and scalability.
• Identifying and driving improvements to increase the Payments Availability, Observability, and Resiliency of Airbnb Payments.
• Developing observability standards/framework for new product readiness to ensure service reliability in SOA and distributed systems.
• Building domain expertise to achieve scalability by understanding the nuances of Payments across processing, compliance, and infra.
• Driving large-scale migration and adoption projects on Observability & Reliability by cross-collaborating with various Payments teams.
• Leading initiatives that promote a culture of reliability throughout the organization by improving incident management platforms and instrumentation.

Requirements:

• 7+ years of experience in back-end software development focusing on large-scale distributed systems.
• BE/B.Tech in Computer Science or a related technical field.
• Strong software development skills in one or more languages such as Java, Python, Kotlin, Scala, or Ruby on Rails.
• Experience in building intelligent AI agents and systems powered by Large Language Models is a plus.
• Evidence of exposure to architectural patterns of a large, high-scale web application (e.g., well-designed APIs, high-volume data pipelines, efficient algorithms).
• Familiarity with cloud platforms like AWS or Google Cloud Platform.
• Deep understanding of software development best practices, including version control, automated testing, CI/CD, and code reviews.
• Experience in incident management, monitoring, alerting, and root cause analysis.
• Effective leadership and communication skills to coordinate cross-functional teams during large-scale projects.
• Experience with initiatives across auto-scaling, self-healing mechanisms, chaos engineering, performance optimization techniques will be a plus.
• Previous experience in AI/ML will also be a plus.

If you are a strong problem solver and have worked in a team that is on-call for production systems before, we encourage you to apply.

XML job scraping automation by YubHub

This role focuses on rapidly developing new features, and working across partner teams to deliver solutions, and maximize impact for Google and top customers.

You will be instrumental in translating cutting-edge AI research into real-world products, and demonstrating the capabilities of latest-generation models.

We are looking for engineers with a strong track record of building and shipping AI-powered software, ideally with experience in early-stage environments where they have contributed to scaling products from initial concept to production.

The ideal candidate will be motivated by the opportunity to drive product & business impact.

Key responsibilities:

• Harness frontier models to drive real-world high-impact outcomes

• Build evaluations, training data, and infrastructure to support AI deployments and rapid iterations

• Collaborate with researchers and product managers to translate research advancements into tangible product features.

• Contribute to the development of best practices for building and deploying generative AI applications.

• Contribute signal to influence the development of frontier models

• Lead the architecture and development of new products & features from 0 to 1.

About you:

In order to set you up for success as a Staff Research Engineer, Applied AI at Google DeepMind, we look for the following skills and experience:

Required Skills:

• Bachelor's degree or equivalent practical experience.

• 8 years of experience in software development, and with data structures/algorithms.

• 5 years of hands-on experience in AI research (e.g. RL, finetuning, evals), AI applications, or model deployment

• Proven experience in rapidly developing and shipping software products.

• Deep understanding of software development best practices, including testing & deployment.

• Experience with cloud computing platforms and infrastructure (e.g., Google Cloud Platform, AWS, Azure).

• Substantial experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Hugging Face, etc.

• Ability to work in a fast-paced environment and adapt to changing priorities.

Preferred Skills:

• Experience with generative AI research or applications.

• Contributions to open-source projects.

• Experience working in, or founding early stage startups.

• Experience delivering software solutions in a fast-paced, customer-facing environment.

If you are a passionate machine learning engineer with a drive to build innovative products and a desire to work at the forefront of AI, we encourage you to apply!

The US base salary range for this full-time position is between $197,000 - $291,000 + bonus + equity + benefits.

XML job scraping automation by YubHub

Your mission is to empower our software engineering team with seamless workflows while securing our production environments.

Responsibilities:

• Build, monitor, and enhance CI/CD pipelines to streamline development workflows and accelerate deployments.
• Design, operate, and maintain scalable, reliable, and secure multi-cloud infrastructures.
• Identify areas for improvement and create innovative solutions that enable high developer velocity.

Team Collaboration & Advocacy:

• Standardize DevOps practices to ensure consistency across all engineering teams.
• Establish measurable KPIs for security performance, reliability, and compliance adherence.
• Partner with development and operations teams to embed security into daily workflows.
• Lead training initiatives to upskill teams on secure coding, threat modeling, and incident response.
• Champion a security-first mindset, driving cultural adoption of DevSecOps principles across the organization.

About you:

• 5+ years of successful experience in a similar role (DevOps, Developer Experience, Platform Engineer, Internal tooling engineer, SRE...).
• Strong proficiency in scripting languages (Go, Python...) and software development best practices.
• Developer experience engineering: developer workflow optimization, tooling, and automation for productivity, real-time developer support, and escalation paths.
• Site Reliability Engineering: CI/CD, containerization, orchestration, infra-as-code, monitoring, logging, alerting, observability...
• Exposure to multi-cloud infrastructures (AWS / GCP / Azure or On-Prem).
• Security Tools & Approaches: OWASP, SAST, DAST, SCA, vulnerability scanners.
• Proven problem-solving and communication skills , ability to contextualize, gauge risks, and get buy-in for high-stakes and impactful solutions.
• Ownership, high agency, and desire to improve things for others.
• Autonomy, self-drive, and ability to work well in a fast-paced startup environment.
• Low ego and team spirit mindset.

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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

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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...)

XML job scraping automation by YubHub

Your mission is to empower our software engineering team with seamless workflows while securing our production environments.

Responsibilities:

• Build, monitor, and enhance CI/CD pipelines to streamline development workflows and accelerate deployments.
• Design, operate and maintain scalable, reliable and secure multi-cloud infrastructures
• Identify areas for improvement and create innovative solutions that enable high developer velocity

Team Collaboration & Advocacy:

• Standardize DevOps practices to ensure consistency across all engineering teams.
• Establish measurable KPIs for security performance, reliability, and compliance adherence.
• Partner with development and operations teams to embed security into daily workflows.
• Lead training initiatives to upskill teams on secure coding, threat modeling, and incident response.
• Champion a security-first mindset, driving cultural adoption of DevSecOps principles across the organization.

About you:

• 5+ years of successful experience in a similar role (DevOps, Developer Experience, Platform Engineer, Internal tooling engineer, SRE...)
• Strong proficiency in scripting languages (Go, Python...) and software development best practices.
• Developer experience engineering: developer workflow optimization, tooling and automation for productivity, real-time developer support and escalation paths
• Site Reliability Engineering: CI/CD, containerization, orchestration, infra-as-code, monitoring, logging, alerting, observability...
• Exposure to multi-cloud infrastructures (AWS / GCP / Azure or On-Prem)
• Security Tools & Approaches: OWASP, SAST, DAST, SCA, vulnerability scanners

Proven problem-solving and communication skills — ability to contextualizing, gauging risks and getting buy-in for high stakes and impactful solutions.

Ownership, high agency and desire to improve things for others.

Autonomy, self-drive and ability to work well in a fast-paced startup environment.

Low ego and team spirit mindset.

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