Fondée en 1999, Scaleway est la filiale cloud du groupe Iliad, l’un des leaders des télécommunications en Europe. Notre mission est de favoriser une industrie numérique plus responsable en aidant les développeurs et les entreprises à créer, déployer et adapter des applications à n'importe quelle infrastructure.
Depuis nos bureaux situés à Paris et à Lille, nous perfectionnons quotidiennement l'écosystème cloud de Scaleway, dont nous sommes les premiers utilisateurs.
Nos quelques 25 000 clients nous choisissent pour notre redondance multi-AZ, notre expérience-utilisateur fluide, nos datacenters neutres en carbone ainsi que nos outils natifs de gestion d'architectures multi-cloud. Nos produits incluent des solutions entièrement gérées pour le bare metal, la conteneurisation et les architectures serverless, offrant ainsi un choix responsable dans le domaine du cloud computing.
Rejoignez notre équipe dynamique de près de 600 collaborateurs venant de divers horizons, dans un environnement stimulant et international alliant excellence technique, créativité et partage.
About the job
The newly established Inference team at Scaleway is on a mission to revolutionize how Machine Learning (ML) is deployed and scaled in the cloud. We are seeking a talented ML Engineer to join us in developing and deploying Large Language Model (LLM) endpoints on both dedicated instances and serverless environments. As we plan to broaden our offerings to include various types of ML models later this year, this role offers a unique opportunity to be at the forefront of ML technology and its application in the cloud.
Reporting to our Manager, Grégoire de Turckheim, you will play a crucial role in building and optimizing ML model deployments, ensuring high performance, scalability, and reliability.
Minimum qualifications
- Proficient in Python and familiar with other programming languages such as Go.
- Strong background in Machine Learning, including experience with LLMs, NLP, or other ML model types.
- Experience with ML frameworks (e.g., TensorFlow, PyTorch) and understanding of MLOps principles.
- Knowledge of deploying ML models in cloud environments, including serverless architectures.
- Familiarity with container technologies (Docker, Kubernetes) and orchestration systems.
- Understanding of REST and gRPC APIs for integrating ML models into applications.
- Excellent command of English, both written and verbal.
Preferred qualifications
- Good understanding of Linux system administration and cloud ecosystems.
Responsibilities
- Optimize ML models for high performance and low latency in cloud environments.
- Design, develop, and maintain scalable and efficient ML model deployments, focusing on LLMs initially and expanding to other models.
- Collaborate with the Inference team to architect and implement serverless solutions for ML model hosting.
- Ensure the reliability, availability, and security of ML model deployments.
- Stay abreast of the latest ML technologies and cloud trends to continuously improve our offerings.
Technical Stack
- Programming Languages: Python, Go
- ML Frameworks: TensorFlow, PyTorch
- Container Technologies: Kubernetes, Docker
- Cloud and Serverless Technologies
- Linux Systems
- Data Storage: S3, PostgreSQL, Redis
- Version Control: Git
Location
This position is based in our offices in Paris or Lille (France)
Recruitment Process
Screening call - 30 mins with the recruiter
Manager Interview - 45 mins
Technical Interviews / or Home Assignment
Team Interview
HR Interview - 45 mins
Offer sent
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