FLOWIT provides a leading GenAI-powered people development platform designed to empower, retain and develop employees, especially frontline workers. We are looking for a Machine Learning (ML) engineer to support our existing AI/ML use cases and drive innovation by exploring, testing, and deploying new use cases in the HR-tech space.
Shape the future of AI in HR: Gain a front-row seat to innovative artificial intelligence applications in the HR tech space.
Advanced AI Integration: Immerse yourself in a cutting-edge AI environment that enhances our innovative people development platform.
Collaborative Culture: Join a team committed to transparency, innovation, and delivering exceptional user experiences.
Career Growth: Thrive in a startup atmosphere where quick growth and learning are prioritized through continuous professional development opportunities.
Work Flexibility: Take advantage of the opportunity to work partly from home and organize your work flexibly. Bonus: 6 Weeks of remote office per year.
Deliver value to our end-users by leveraging ML and AI technology for advancing our FLOWIT platform.
You will work on process optimization, productionalization of AI services, and both ideating and developing new AI functionality for FLOWIT’s AI-driven platform.
You will be developing and maintaining productive data processing pipelines.
Optimization, fine-tuning, and maintenance, such as output monitoring and retraining of ML models and AI services, including prompt engineering and fine-tuning of LLMs.
Proven experience (2+ years) as a ML/AI Engineer, Data Scientist, Software Engineer or in a similar role.
Strong proficiency in programming with Python and the most important packages. Proficiency in SQL. Experience in Bash/Shell scripting is a plus.
Master's degree in Data Science, Computer Science, Statistics or a quantitative discipline, or equivalent practical experience.
Practical experience working with Large Language Models, ideally in production setups.
Hands-on experience with cloud services (AWS, Azure, GCP).
Experience with orchestration tools like Airflow and container technologies like Docker.
Excellent problem-solving skills, with a methodical approach to troubleshooting and project management. Ability to break down complex problems.
Business acumen and customer-centric view, ability to evaluate and consider technical decisions from the view of and impact on the end-user.
Fluent in English; proficiency in German is advantageous but not mandatory.
Excellent communication and teamwork with technical and non-technical colleagues.