Job
- Level
- Experienced
- Location
- Mülheim-Kärlich
- Working Model
- Hybrid, Onsite
- Job Field
- Software, Data
- Employment Type
- Full Time
- Contract Type
- Permanent employment
Job Summary
In this role, you will develop ML systems, implement end-to-end pipelines, optimize models for cloud deployment, work on secure data platform integration, and support teams in model delivery.
Job Technologies
Your role in the team
- As a Machine Learning Engineer, you develop, implement, test, deploy, and maintain data- and model-centric systems that provide machine learning functionalities at a production level.
- Development of end-to-end ML training pipelines (data collection, validation, transformation, training, and evaluation)
- Provision, optimization, and packaging of models for production deployment
- Support of the platform team in deploying models in the cloud
- Support for the AI Runtime team in deploying models on edge systems or sorting machines
- Participation in data- and model-centric research as well as innovation projects
- Development, integration, and maintenance of secure data platforms (e.g., SQL/NoSQL databases, object storage, feature stores)
- Ensuring data security, data protection, and compliance requirements
- Design and development of REST APIs for providing ML services and data platform functionalities
- Development and maintenance of internal tools and web-based user interfaces to support ML workflows
- Application of proven software development practices for version control, code reviews, and technical documentation
- Development of robust and maintainable software, including unit, integration, and performance testing, as well as knowledge transfer
- Containerization of components and implementation of CI/CD pipelines
- Maintenance and troubleshooting of ML tools in production environments
- Close collaboration and coordination with internal users and stakeholders
- We expect a high level of personal responsibility for the projects managed, including stakeholder management, requirements management, project control, and technical decision-making.
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Our expectations of you
Qualifications
- Excellent knowledge of Python
- Extensive expertise in the field of computer vision as well as machine learning and deep learning tooling
- Knowledge of TypeScript, REST API development, and modern frontend frameworks (e.g., Vue.js or React) or willingness to learn them
- Knowledge of cloud and on-premises platforms as well as their interfaces
- Knowledge of model optimization frameworks (TensorRT, ONNX, CUDA, cuDNN) as well as edge deployment on hardware platforms (x64, ARM/Jetson)
Experience
- Several years of proven professional experience in the development and deployment of productive machine learning systems with measurable business benefits
- Experience with MLOps, especially data modeling, packaging, containerization, and CI/CD
- Experience in Data Science for optimizing image processing models
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What we offer
- Modern technologies and AI-based systems
- A practical engineering environment with direct impact on the performance of our machines
- Close collaboration with international teams
- Open corporate culture with flat hierarchies and short decision-making processes
- Norwegian-influenced corporate culture with an open 'you' mentality
- The opportunity to actively shape future machine developments
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Topics You Will Work On
Job Locations
About Your Employer
Tomra Recycling
TOMRA Recycling, a division of the TOMRA Group, focuses on automated sorting and recovery technologies. Based in Mülheim-Kärlich, Germany, the company assists customers worldwide in sorting and recycling materials more efficiently.
Description
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Industry, Production
Machine Learning Engineer
- Location
- Mülheim-Kärlich
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
