Main tasks and responsibilities

• Being comfortable with experimentation and willing to approach a problem in multiple ways via rapid prototyping.

• Identifying appropriate datasets and driving annotation for machine learning techniques.

• Developing (together with relevant expert talents) and maintaining machine learning applications and products.

• Iteratively (re-)training the developed models and running evaluation experiments in collaboration with others, as well as performing statistical analysis of results.

• Keeping an eye on state-of-the-art machine learning solutions, emerging technologies, and developments in academia.

• Translating and communicating technical concepts and solutions to different stakeholders.

Key requirements

Education Level
Bachelor’s or advanced degree in Computer Science, Artificial Intelligence, Mathematics, or a related field.

Technical Skills:

• Expertise in the Scala programming language and the Play Framework is desired, but not mandatory.

• Advanced Elasticsearch experience.

• Postgres database or other relational database experience.

• Experience in content apps.

• Experience in microservices.

• Knowledge of a variety of AI techniques - such as natural language processing, classification, clustering, optimization, and deep neural networks - along with a solid understanding of their mathematical foundations and real‑world advantages and drawbacks, is preferred.

• Knowledge of data structures, semantic extraction, and text representation in an NLP context.

• Proficiency in Python (OOP) preferred.

• Experience in using technologies such as Docker. Azure, GCP, and AWS.

• Experience in creating APIs (RESTful, Asynchronous, etc.).

• Familiarity with the concepts and applications of LLMs is a plus.

• Ability to write clean, production-ready code.

Other Skills:

• Fluency in English is required. Any additional language skills are an asset.