Scaleway

About the Company

European. Cloud. AI.

Founded in 1999, Scaleway is a pioneer in European cloud computing, providing a complete ecosystem to build, train, deploy, and scale AI models and cloud-native applications. We offer sovereign, sustainable, and high-performance infrastructure designed for today's tech-driven world.

Key figures:

- 20+ years of expertise in cloud infrastructure
- 80+ innovative cloud products and services
- 9 renewable energy-powered data centers
- 65 points of presence worldwide
- Industry-leading PUE of 1.15, the lowest in Europe
- 550+ cloud experts across Europe
- 38,000+ customers in 160 countries

From startups to enterprises, Scaleway helps you accelerate innovation while maintaining data sovereignty and sustainability. We are proud to be the European alternative to hyperscalers.

Listed Jobs

Company Name

Scaleway

Job Title

Site Reliability Engineer - H/F

Job Description

**Job title:** Site Reliability Engineer **Role Summary:** Architect, build, and maintain highly available, scalable infrastructure and release pipelines for high‑traffic digital products. Drive automation via IaC, CI/CD, and GitOps while ensuring observability, security, and performance across hybrid cloud and on‑prem environments. **Expectations:** - Deliver reliable, secure, and performant services. - Enable rapid deployment of features with minimal interruption. - Continuously improve tooling, practices, and documentation. - Collaborate closely with product and engineering teams to translate business needs into technical solutions. **Key Responsibilities:** - Design, implement, and maintain IaC with Terraform and Ansible for shared platform components. - Own CI/CD pipelines in GitLab CI, ArgoCD, Helm, and Kubernetes; support dev teams (~25 % of time). - Containerize services using Docker; orchestrate via Kubernetes. - Configure and evolve monitoring stack (ELK, Grafana, OpenTelemetry, Plausible). - Execute load/testing with K6; analyze results for capacity planning. - Enforce security and quality through Trivy, SonarQube, Playwright, and other checks. - Participate in product backlog grooming, technical scoping, and cross‑team communication (Vitrine, Tunnel, Espace Abonné, Assistance). - Mentor junior SREs, contribute to knowledge base, and promote DevSecOps culture. **Required Skills:** - **Infrastructure & Automation:** Terraform, Ansible, GitOps. - **CI/CD & Release:** GitLab CI, ArgoCD, Helm, Kubernetes, Docker. - **Monitoring & Observability:** ELK stack, Grafana, OpenTelemetry, Plausible. - **Performance & Security:** K6 load testing, Trivy, SonarQube, Playwright. - **Programming & APIs:** Python, Node.js (front/web/API concepts). - **Environments:** Linux, hybrid cloud (Scaleway + on‑prem). - **Soft Skills:** Autonomous problem‑solving, product‑centric mindset, collaboration, curiosity, pragmatic troubleshooting. **Required Education & Certifications:** - Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. - Professional certifications preferred: Certified Kubernetes Administrator (CKA), Terraform Associate, DevOps Foundation, or equivalent. - 3+ years of SRE/DevOps experience in a hybrid cloud/on‑prem setting.

Montpellier, France

Hybrid

Senior

31-10-2025

Company Name

Scaleway

Job Title

Site Reliability Engineer - SRE Toulouse

Job Description

**Job Title** Site Reliability Engineer **Role Summary** Drive the reliability and scalability of cloud services by building and maintaining tooling, monitoring, and automation that enable rapid incident discovery, resolution, and continuous improvement across multi‑AZ environments. **Expectations** - Act as a trusted reliability partner to engineering teams worldwide. - Own production systems at scale, delivering high uptime and low MTTR. - Continuously evaluate and enhance SRE processes, tooling, and infrastructure. - Maintain strong collaboration with developers, operators, and product owners. **Key Responsibilities** - Design, develop, and maintain automation scripts, tooling, and documentation for incident detection, diagnosis, and remediation. - Lead on‑call rotation, triage high‑impact incidents, and coordinate response across teams. - Implement and evolve observability solutions (metrics, logs, traces) to ensure proactive monitoring. - Manage lifecycle of production services, applying best practices for stability, resilience, scalability, security, and performance. - Advocate for and apply infrastructure‑as‑code, CI/CD, and configuration management to reduce manual effort. **Required Skills** - Proficient in Go, Python, or Rust with strong coding and debugging ability. - Experience in Linux system administration (Ubuntu/Debian/CentOS) and scripting (Bash, Python). - Hands‑on knowledge of cloud/virtualization stack: bare metal, VMs, containers, orchestrators. - Solid understanding of TCP/IP, DNS, load balancing, IPv6, BGP, and network virtualization. - Ability to troubleshoot production‑level failures and document solutions clearly in English. **Preferred Skills** - Experience with infrastructure‑as‑code (Terraform, Ansible, etc.) and continuous deployment pipelines. - Familiarity with monitoring/logging stacks (Prometheus, Grafana, Sentry, ELK). - Background administering relational databases (PostgreSQL). - Exposure to physical hardware automation and cloud‑specific use cases. **Required Education & Certifications** - Bachelor’s degree in Computer Science, Engineering, or equivalent experience. - No specific certifications mandatory, but relevant cloud or DevOps credentials (e.g., AWS/Azure/GCP, Kubernetes, Terraform) are advantageous.

Lille, France

Hybrid

02-11-2025

Company Name

Scaleway

Job Title

AI Engineer - Sales

Job Description

**Job title** AI Engineer – Sales **Role Summary** Design, build, and maintain AI‑powered tools that amplify sales effectiveness. Lead end‑to‑end development of LLM‑based applications, data pipelines, and agentic workflows, ensuring production readiness and continuous improvement through evaluation and feedback loops. **Expectations** - Deliver scalable AI solutions that directly impact sales performance. - Iterate quickly from prototype to production while maintaining high quality standards. - Communicate effectively with Sales, Product, and Operations stakeholders in French and English. **Key Responsibilities** - Develop, deploy, and maintain ML/DL/LLM pipelines using Python, FastAPI, Scikit‑learn, Pandas, NumPy. - Integrate LLM frameworks (LangChain, LlamaIndex) and implement retrieval‑augmented generation, vector search, and search infrastructure. - Execute model evaluation, create feedback loops, and tune performance. - Build and manage CI/CD, Docker, Nginx, and MLOps/LLMOps pipelines for production deployment. - Occasionally leverage Go or JavaScript for quick prototyping or integration tasks. - Collaborate cross‑functionally with Sales, Product, and Operations to transform prototypes into deliverables. **Required Skills** - Minimum 2 years hands‑on experience with Data Science / AI solutions, including LLM implementations. - Proficient in Python for data handling, ML pipelines, and application development. - Deep understanding of LLM capabilities, limitations, and embedding strategies. - Experience with LangChain or LlamaIndex. - Solid knowledge of RAG techniques, vector databases, and search systems. - Strong model evaluation and performance‑tuning skills. - MLOps/LLMOps expertise: version control, CI/CD pipelines, Docker, deployment. - Bonus: familiarity with Go or JavaScript. - Excellent communication in French and English; ability to translate technical concepts for non‑technical audiences. **Required Education & Certifications** - Bachelor’s degree (or equivalent) in Computer Science, Data Science, or related technical field. - Certifications in relevant AI or machine‑learning technologies are advantageous but not mandatory.

Paris, France

Hybrid

Junior

02-11-2025

Company Name

Scaleway

Job Title

Stage Ingénieur ML/LLM - Paris - H/F

Job Description

**Job title** ML/LLM Engineer Intern **Role Summary** Assist in developing a conversation‑assistant to support technical agents by fine‑tuning, evaluating, and deploying large language models (LLMs). Work with real customer‑support conversations, experiment on high‑performance GPUs, and collaborate cross‑functionally with support staff and ML experts. **Expectations** * Deliver working LLM pipelines in a fast‑paced, autonomous environment. * Communicate progress, results, and technical decisions in clear documentation. * Use cloud GPUs and MLOps tooling to accelerate experimentation. **Key Responsibilities** 1. Design, fine‑tune, and evaluate LLMs for NLP tasks such as intent classification, response generation, and ticket summarisation. 2. Build and maintain data pipelines that ingest, clean, and label noisy conversational data. 3. Run experiments on GPU H100 infrastructure, managing training parameters and monitoring performance. 4. Collaborate with technical agents to define user needs, review outputs, and iterate solutions. 5. Document methodologies, results, and reproducibility protocols for knowledge transfer. 6. Mentor or collaborate with peers on ML best practices and emerging LLM techniques. **Required Skills** * Current study in engineering, data science, AI, or computer science (final year of master or engineering school). * Strong grasp of supervised ML fundamentals, model evaluation, over‑fitting prevention, and data pipelines. * Hands‑on experience with transformers/LLMs using Hugging Face and NLP tasks (classification, tagging, generation). * Proficiency in Python (pandas, scikit‑learn) and deep‑learning frameworks (PyTorch or TensorFlow). * Familiarity with noisy text data processing and prior NLP projects. * Knowledge of modern LLM fine‑tuning methods (LoRA, QLoRA), Retrieval‑Augmented Generation, advanced prompting, and automated evaluation. * Comfortable using cloud platforms (AWS, GCP, Scaleway) and MLOps tools (Weights & Biases, MLflow). * Strong written and verbal communication, English‑technical literacy. * Demonstrated curiosity, autonomy, rigor, and collaborative mindset. **Required Education & Certifications** * Final year of a master’s program or engineering school in computer science, data science, AI, or equivalent. * No specific certifications required, but experience with cloud or MLOps platforms is a plus.

Paris, France

On site

05-11-2025