(Senior) Machine Learning PlatformOps Engineer, RemoteEurope (fmx)

Berlin - Germany

Monthly Salary: Not Disclosed

Posted on: 16 hours ago

Vacancies: 1 Vacancy

Job Summary

Own the ML lifecycle: Design implement and maintain robust containerized and reproducible pipelines for model training evaluation and deploymentacross 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
Marija Dimitrova

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

Remote Work :

Yes

Employment Type :

Full-time

Own the ML lifecycle: Design implement and maintain robust containerized and reproducible pipelines for model training evaluation and deploymentacross both batch and real-time settings.Operationalize models at scale: Build and manage ML services APIs and model serving infrastructure using tools like...

Own the ML lifecycle: Design implement and maintain robust containerized and reproducible pipelines for model training evaluation and deploymentacross 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
Marija Dimitrova

#LI-A1

Remote Work :

Yes

Employment Type :

Full-time

Key Skills

Industrial Maintenance
Machining
Mechanical Knowledge
CNC
Precision Measuring Instruments
Schematics
Maintenance
Hydraulics
Plastics Injection Molding
Programmable Logic Controllers
Manufacturing
Troubleshooting

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About Company

AUTO1 Group

AUTO1.com is Europes largest wholesale platform for used cars. More than 60,000 partner dealers in over 30 countries actively digitize their used car business with AUTO1.com technologies and services. Buyers have access to a cross-brand inventory of over 30,000 inspected used cars. S ... View more

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