(Senior) Machine Learning Platform/Ops Engineer, Remote/Europe (f/m/x) at AUTO1 Group

Carnaxide, , Portugal -

Full Time

Start Date

Immediate

Expiry Date

08 Mar, 26

Salary

0.0

Posted On

08 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

MLOps, Machine Learning, Python, CI/CD, Docker, Terraform, Jenkins, AWS, GCP, Azure, Monitoring, Collaboration, Model Serving, APIs, Feature Store, Data Science

Industry

technology;Information and Internet

Description

Company Description We are seeking an experienced (Senior) Machine Learning Platform/Ops Engineer with a passion for designing, deploying, and maintaining scalable, resilient, and reproducible machine learning infrastructure. You will play a pivotal role in operationalizing ML solutions in close partnership with both data scientists and engineers. AUTO1 Group Technology drives innovation in the used car market across Europe. You will work at the intersection of software engineering, data science, and DevOps, helping bring state-of-the-art ML models—such as large-scale recommendation systems and transformer-based neural networks—safely into production. Job Description Job 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. Qualifications 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. Additional Information 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 Contact Maryam Anwar At AUTO1 Group we live an open culture, believe in direct communication, and value diversity. We welcome every applicant; regardless of gender, ethnic origin, religion, age, sexual identity, disability, or any other non-merit factor. #LI-A1

Responsibilities

You will own the ML lifecycle by designing, implementing, and maintaining robust pipelines for model training and deployment. Additionally, you will operationalize models at scale and ensure their reliability and quality through CI/CD practices.