Site Reliability Engineer, Mistral AI
+ Equity
Visa sponsorship available
Generative AI model developers
Open for applications
Generative AI model developers
101-200 employees
Open for applications
+ Equity
Visa sponsorship available
101-200 employees
Company mission
To make frontier AI ubiquitous, and to provide tailor-made AI to all the builders.
Role
Who you are
- 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...)
What the job involves
- 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
- 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
Our take
Founded by Facebook AI researchers, Mistral AI focuses on developing open-source generative AI models to "make AI useful." It emerged in early 2023, quickly achieving a $260 million valuation.
With the upcoming release of Mixtral in 2024, featuring up to 176 billion parameters, Mistral is under pressure to deliver. Mixtral's open-source nature has sparked concerns about potential misuse, yet Mistral remains a formidable competitor in the AI landscape, challenging models from Google and Meta.
Recently, Mistral secured a massive $640 million funding round, raising its valuation to $6 billion. This Series A funding, led by General Catalyst and including investors like Lightspeed Venture Partners and Andreessen Horowitz, underscores significant interest in alternatives to ChatGPT.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 4 rounds)
Jun 2024
$515.3m
SERIES B
Feb 2024
$16.6m
SERIES A
Total funding: $1.1bn
Company benefits
- Competitive bonus structure
- Equity
- Opportunities for professional growth and development
Company HQ
Villette, Paris, France
Leadership
Timothee Lacroix
(CTO)Previously PhD and Software Engineer Intern at Facebook and Visiting Undergraduate at CAlab UCSD
Guillaume Lample
(Chief Scientist)Research Student and Scientist at Facebook AI and Research Intern at Jane Street Capital
Arthur Mensch
(CEO)Previously Staff Research Scientist at DeepMind, Post-doc researcher at École normale supérieure, Visiting Researcher at NYU Courant Institute of Mathematical Sciences and PhD Student at Inria
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