About the Role
As a Machine Learning Engineer at Regnology, you will be an integral part of our international and agile IT team. Your role will involve combining technical expertise with regulatory know-how to develop innovative AI/ML solutions for both internal and external users. You will be responsible for selecting, training, and tweaking AI models using various datasets in an MLOps approach. Additionally, you will contribute to new architectural approaches for AI models to accomplish tasks in the fields of NLP (LLMs), classification, and regression.
Responsibilities
- Model Development: Select, train, and optimize AI models using diverse datasets.
- Data Management: Scrap, map, and implement data automation pipelines for preprocessing.
- Team Collaboration: Work in a multicultural, international team in an agile environment to build AI/ML-based solutions in our product landscape or introduce new products.
Why You Should Join Us
- Growth Opportunities: Our start-up character allows you to design our future and take on significant responsibilities.
- Flexible Work Environment: We promote remote working and flexible hours to ensure a positive work-life balance.
- International Exposure: Participate in international projects and collaborate with teams across different locations.
- Professional Development: Benefit from numerous individual and wide-ranging training opportunities, alongside our buddy-program.
- Positive Culture: Enjoy a supportive team atmosphere with transparent communication across all levels.
Ideal Candidate
- Education: Successfully completed university studies in machine learning, computer science, mathematics, or a similar area.
- Experience: At least 1 year of experience in full machine learning/AI development (in Python or R) and MLOps principles.
- Technical Skills: Proficiency in relational databases (PostgreSQL, Microsoft SQL Server, MySQL, Oracle) and backend services (Java, Python, R).
- Additional Skills: Experience in modern web technologies (e.g., Angular, TypeScript), DevOps principles for Containers, Helm, and K8s, and hands-on experience in GCP, Azure, or AWS for MLOps is advantageous.
How to Apply
To apply for this exciting opportunity, please send your CV to our recruiting team. We look forward to meeting you in a personal or virtual interview. Your privacy is important to us, and we will treat your application confidentially.
Benefits Extracted with AI
- Remote working
- Flexible working hours
- International projects
- Training opportunities
- Positive work-life balance
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