Backend Engineer

il y a 1 jour

Paris, France :probabl. Temps plein

About Probabl Probabl is the official and exclusive industrial operator of scikit-learn, the world's most widely used machine learning library. Born from the open‑source ecosystem, we are building a comprehensive suite of tools, starting with Skore. Our mission is to help data teams design, track, and validate models through a unique code‑first UX, prioritizing ease of use and flow. The Role As a Backend Engineer, you will build the backbone of Skore, ensuring our platform is robust, scalable, and secure. Beyond the core product, you will support our Go‑to‑Market strategy by building and deploying services (billing, licensing, telemetry, and MLOps tools) that provide simple and direct value to data scientists. You will join a team that values curiosity, collaboration, and high‑quality engineering standards. Responsibilities Design and implement scalable backend systems, including data models, APIs, and event‑driven architectures. Develop specific integrations to support commercialization (e.g., billing, licensing servers, usage telemetry) and specialized MLOps services. Implement authentication and authorization workflows using OIDC/OAuth2 concepts (integrating with ORY). Apply Clean and Hexagonal architecture principles to ensure code maintainability and testability. Understand and integrate with existing DevOps infrastructure; deploy and orchestrate your services within our Kubernetes environment. Technical Environment Core: Python, FastAPI, PostgreSQL, Redis, S3. Infrastructure: Kubernetes, Docker, Helmfile. Auth: Ory (Kratos/Hydra), OIDC, OAuth2. Frontend Context: Vanilla Vue.js (knowledge helpful for collaboration, not required for coding). Requirements Experience Level: Early Senior to Senior (approx. 5+ years). We prioritize depth of understanding and pragmatic engineering over specific year counts. Backend Engineering: Strong experience designing and developing enterprise backends (REST APIs, asynchronous tasks, third‑party integrations). Architecture Patterns: Familiarity with Hexagonal/Clean Architecture and Event‑Driven patterns (EIP). Identity & Access: Solid understanding of authentication and authorization concepts (OIDC, OAuth2). Mindset: Strong focus on collaboration, high‑quality requirements, and curiosity. Preferred Qualifications Experience building scalable systems for data science or machine learning platforms. Contributions to open‑source projects or active participation in the open‑source community. Working Conditions Location: Paris, Saclay Presence: Office‑based or Hybrid Team: Tech & Product Department / Applications Engineering Team Supervisor: VP of Applications Engineering Stakeholder Interaction: Regular collaboration with Product Management, Labs and Engineering. Cultural Fit: Align with the company's values of innovation, agility, and user‑centricity in a fast‑paced startup environment. #J-18808-Ljbffr

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