Senior Machine Learning Platform/Ops Engineer

il y a 16 jours

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AUTO1 Group

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B2C • Marketplace • Transport

AUTO1 Group est la plateforme automobile numérique leader en Europe pour l’achat et la vente en ligne de voitures d’occasion. Nous offrons aux consommateurs et aux professionnels de l’automobile dans toute l’Europe continentale un moyen simple et rapide de vendre et d’acheter des voitures d’occasion à des prix fixes, sans négociation, via nos plateformes établies. Nous proposons la plus large sélection de voitures d’occasion dans plus de 30 pays, couvrant plus de 80 marques et toutes les gammes de prix. AUTO1 Group a vendu plus de 615 000 véhicules via nos sites et applications en 2019.

5001 - 10000 employés

Fondée en 2012

👥 B2C

🏪 Place de marché

🚗 Transport

💰 Convertible Note en 2020-07

Description

• Own the ML lifecycle: Design, implement, and maintain robust, containerized, and reproducible pipelines for model training, evaluation, and deployment—across both batch and real-time settings. • Operationalize models at scale: Build and manage ML services, APIs, and model serving infrastructure using tools like MLflow, Amazon SageMaker, and Feature Store. • Automate and monitor: Set up and maintain monitoring, observability, and alerting systems to ensure high availability and performance (including model/data drift, feature logging, and inference latency). • Accelerate experimentation: Develop and maintain internal libraries, templates, and platform tooling to improve reproducibility and simplify deployment workflows for all model teams. • Ensure reliability and quality: Implement CI/CD pipelines for model and data workflows using Docker, Terraform, and Jenkins and share best practices, mentor less experienced engineers, and foster strong collaboration across teams. • Stay current: Continuously evaluate emerging MLOps technologies to improve efficiency, scalability, and reliability.

🎯 Exigences

• Hands-on MLOps experience: 2+ years production experience operationalizing, deploying, monitoring, and maintaining ML models at scale. • Tooling: Proficient with infrastructure-as-code, CI/CD systems (Docker, Terraform, Jenkins, or equivalent), and at least one major cloud provider (AWS, GCP, or Azure). • Programming: Strong Python skills (including ML libraries such as scikit-learn, LightGBM, PyTorch, TensorFlow; plus experience with SQL). • Monitoring: Familiar with monitoring and logging for ML pipelines (model drift detection, data validation, performance/feature logging). • Collaboration: Effective communicator with experience partnering across engineering and data science. • Bonus: Experience with feature stores, model version management, or building internal ML platforms.

🏖️ Avantages

• Working from home: you can work from home up to 5 days a week • International teams • Educational budget to support your continuous learning and development • Personal growth with the contribution of own ideas • Exciting team events like Hackathons to foster collaboration and innovation • Discounts at Autohero, our platform for high-quality used cars