
Noesis
We are an international technology consultancy with a thousand talents specialized in different technologies. Every day, we work together to create innovative solutions that impact society. We are in Portugal, Spain, the Netherlands, Brazil, Ireland, and the USA. It is in cultural diversity and opportunities that we find the motivation to innovate and challenge ourselves to be better.
About company Data scientist - Lisbon/hybrid
Remote
Lisbon
April 9, 2026
Full-time
24k-30k EUR
Noesis is looking for professionals with the following profile:
Responsibilities:
- Design, develop and maintain machine learning solutions in Python
- Conceive, test and optimize prompts for LLMs
- Implement and manage the deployment of machine learning models
- Build and maintain data and training pipelines for LLMs
Requirements:
- Bachelor's degree in Software Engineering, Computer Engineering or similar;
- More than 2 years of experience as a Data Scientist;
- Experience in the use and deployment of Large Language Models (LLMs);
- Experience in Prompt Engineering and Prompt Design;
- Experience in LargeChain and other LLM management frameworks;
- Know-how in Azure OpenAI (valued);
- Know-how in Google VertexAI (valued);
- Experience in developing machine learning projects (Python);
- Experience with relational databases and NoSQL;
- Knowledge of Agile methodology, Jira and Confluence tools (valued);
- Commitment to quality deliveries;
- Knowledge of English (mandatory);
- Written and verbal communication skills;
- Ability to work in a collaborative and productive environment;
- Critical analysis and problem-solving skills.
Work regime:
2x per week (Lisbon)
If you meet these requirements and would like to join an innovative organization that continuously invests in the training of its talents, send us your application.
Join us. Let’s innovate together!
All our recruitment and selection processes are based on equal opportunities, valuing the competence and potential of each person and ensuring that no candidate is discriminated against based on gender, ethnicity, sexual orientation, age, religion or physical condition.