Inhalte der Stellenbeschreibung
We are looking for someone to join our team who is either at the beginning of their career in machine learning or has already gained some professional experience. What matters most is a solid foundation, curiosity and the motivation to learn how ML systems are built and operated in practice.You will work in a hybrid setup based in Hamburg, Dresden, or Berlin, spending two days per week in the office. In this role, you will also collaborate closely with colleagues across different time zones, including the US East Coast.
Minimum Qualifications and skills
- A solid foundation in machine learning concepts and model evaluation, gained through study, training or practical/professional experience.
- Practical Python skills and the ability to write clear, maintainable code.
- Experience working with data and SQL..
- Some hands-on experience developing an ML solution.
- Interest in learning how models and data pipelines are deployed, monitored and improved in production.
- A structured approach to problem-solving.
- Clear communication skills and an open, collaborative working style.
- Working proficiency in English.
Preferred Qualifications and skills
- Initial experience with Docker or another containerization tool.
- Exposure to AWS, GCP or another cloud platform.
- Familiarity with NLP, large language model applications or AI agents.
- Experience with NoSQL databases, distributed data processing or streaming technologies.
- Awareness of software engineering practices such as version control, testing and continuous integration.
- Experience operating, monitoring or troubleshooting an ML model or data pipeline.
What you can expect
- Together with experienced colleagues, you translate product and business questions into well-defined machine learning tasks.
- You develop, evaluate, and improve machine learning models using Python.
- You contribute to reproducible data and ML pipelines, from initial experimentation through to production deployment.
- You prepare services and batch jobs for deployment using tools such as Docker.
- You work with cloud-based ML environments in AWS or GCP.
- You use SQL to explore, prepare, and validate data.
- You monitor model performance, investigate issues, and help improve the reliability of production solutions.
- You document your work and clearly communicate assumptions, trade-offs, and results.
- You collaborate closely with colleagues across Data Engineering, Software Engineering, Product, and other business functions.
- You consider model quality, robustness, and fairness when developing and evaluating solutions.
At ParshipMeet, we help millions of people around the globe meet, date, and fall in love. We want our teams to be as diverse as our customer base. Constantly adding new perspectives is key to our success. We will never judge anyone by age, sex, family background, color of skin, religious beliefs nor sexual orientation. For us, it’s all about skills, competencies, and you as a human being!