Senior Machine Learning Platform/Ops Engineer

🔥 13 hours ago

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B2C • Marketplace • Transport

AUTO1 Group is Europe's leading digital automotive platform, specializing in the buying, selling, and financing of used cars. The company utilizes a range of products and services to maximize value for both car dealers and consumers, including Europe-wide platforms for purchasing and remarketing cars. AUTO1 Group also offers digital financing solutions and aims to enhance the consumer experience through its brands, AUTO1. com and Autohero.

📋 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.

🎯 Requirements

• 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.

🏖️ Benefits

• Working from home: you can work from home up to 5 days a week • 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