Job
- Level
- Senior
- Job Field
- Software, Data
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Location
- Mülheim-Kärlich
- Working Model
- Hybrid, Onsite
Job Summary
In this role, you will develop platforms and tools for the machine learning lifecycle, build ML training pipelines, and create REST APIs to deliver ML services while collaborating closely with data and MLOps teams.
Job Technologies
Your role in the team
- As a Senior Python Software Engineer, you will develop, operate, and scale the technical platforms, services, and tools that support the entire machine learning lifecycle.
- You lay the foundation for data collection, model training, deployment, and operation, working at the interface between software engineering, data platforms, MLOps, and machine learning.
- The focus of this role is on developing production-ready software solutions, platforms, and workflows.
- The daily work mainly consists of software development, architecture, automation, and integration, rather than training machine learning models.
- Typical tasks include:
- Machine Learning Engineering
- Development of end-to-end ML training pipelines (data collection, validation, transformation, training, and evaluation)
- Deployment, optimization, and packaging of models for inference 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
- Data Management
- Development, integration, and operation of secure data platforms (e.g., SQL/NoSQL databases, data warehouses, object storage, and feature stores)
- Ensuring Data Security, Privacy, and Compliance
- Services & ML Tooling
- Design and implementation of REST APIs for providing ML services and data platform functionalities
- Development and maintenance of internal tools as well as web-based user interfaces to support ML workflows
- Software Engineering
- Application of proven software engineering practices for version control, code reviews, and precise 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
- Operation and troubleshooting of ML tools in production environments
- Close collaboration and coordination with our internal users
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Our expectations of you
Qualifications
- Excellent knowledge of Python
- Solid 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 developing and deploying 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 paths
- Norwegian-influenced corporate culture with an open Du-mentality
- The opportunity to actively shape future machine developments
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Benefits
Health, Fitness & Fun
Work-Life-Integration
Topics You Will Work On
Job Locations
About Your Employer
Tomra Sorting GmbH
TOMRA was founded in 1972 with a innovative design for reverse vending machines (RVMs) that could automatically collect beverage containers. This innovative idea has led TOMRA to become a leader in manufacturing and selling RVMs all over the world.
Description
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Industry, Production, Power Sector, Economy