Public summary
Seeking a Machine Learning Engineer to develop, train, evaluate, and deploy machine learning models for business and logistics use cases. Collaborate with data scientists, software engineers, and business stakeholders to create scalable solutions. Build and maintain data pipelines and oversee machine learning model production and monitoring. Contribute to platform and API design, document technical processes, and promote best practices. Requires degree in relevant fields and professional experience with machine learning deployment. Fluent English required. Offers permanent contract, development opportunities, home office options, attractive salary and benefits, and a supportive work environment in a globally active logistics company.
Location and work setup
- Location
- Hamburg
- Remote status
- Hybrid
- German requirement signal
- No German Required Detected
- Detected job language
- English
Salary
EUR 60000.00 - 70000.00 YEAR
Responsibilities
Develop, train, evaluate, and deploy machine learning models for real-world business and logistics applications. Collaborate across disciplines to translate challenges into scalable technical solutions. Build and maintain data pipelines and feature engineering processes for training and production. Productionize models using software engineering best practices. Monitor model performance, data quality, and detect model drift. Contribute to design of ML platforms, APIs, and data products. Document models, assumptions, processes, and results. Support best practices in machine learning, software development, testing, version control, and deployment. Stay updated on AI, machine learning, cloud technologies, and responsible AI.
Qualifications
Degree in Computer Science, Data Science, Mathematics, Statistics, Engineering, or related field. Professional experience in developing and deploying machine learning solutions. Solid understanding of machine learning concepts, model evaluation, statistics, and data preparation. Familiarity with cloud platforms and modern machine learning infrastructure. Strong analytical and problem-solving skills. Ability to communicate technical concepts clearly to both technical and non-technical stakeholders. Fluent in English (written and spoken).