ESA Graduate Trainee in AI/Machine Learning Software Engineering at ESA

Paris, Ile-de-France, France -

Full Time

Start Date

Immediate

Expiry Date

02 May, 26

Salary

0.0

Posted On

01 Feb, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Machine Learning, Data Engineering, Natural Language Processing, Anomaly Detection, Classification, Regression, Linux, Git, CI/CD, Docker, Singularity, Communication, Teamwork, Problem Solving, Interpersonal Skills

Industry

Space Research and Technology

Description

Location ESA Headquarters, Paris, France Our team and mission You will join the Data Management Unit within the IT Department at ESA Headquarters, Paris. We run the ESA Data and Apps Factory, the Agency's largest corporate data repository. By providing trusted, accessible data, we enable ESA to take decisions and improve processes based on knowledge rather than intuition. We are an experienced team that delivers end-to-end, combining infrastructure, data engineering, data science, and operations. To generate insight and digitalise business processes, we apply AI/ML to time-series analysis, natural language processing, and more. We own and operate the entire technology stack for Machine Learning Operations. This ensures that the models we build translate into secure, reliable, and actionable outcomes across the Agency. You are encouraged to visit the ESA website: http://www.esa.intField(s) of activity/research for the traineeship You as an AI/ML Software Engineer will develop AI models and integrate them into software applications to improve the Agency's business processes. Key responsibilities: You will work with ESA's largest corporate data repository, which includes structured data (SQL databases) and unstructured data (documents). Building on this foundation, you will develop a wide range of AI models, such as anomaly detection, classification and regression, and natural language processing using LLMs. You will be involved end-to-end across the pipeline: data engineering, model development, testing and operations, and integration with existing corporate software. You will also communicate your results to senior management and present your work at internal and external conferences.Technical competencies Knowledge of relevant technical/functional domainsRelevant experience gained during internships, project work and/or extracurricular or other activitiesGeneral knowledge of the space sector and relevant activitiesKnowledge of ESA and its programmes/projectsBehavioural competencies Result Orientation Operational Efficiency Fostering Cooperation Relationship Management Continuous Improvement Forward Thinking For more information, please refer to the ESA Core Behavioural Competencies guidebookEducation You should have just completed, or be in the final year of your master’s degree in Computer Science or similar (Mathematics, Physics, Engineering, etc.).Additional requirements You should have good interpersonal and communication skills and should be able to work in a multicultural environment, both independently and as part of a team. Previous experience of working in international teams can be considered an asset. Your motivation, overall professional perspective and career goals will also be explored during the later stages of the selection process. You should also have: Knowledge of: Python Machine Learning Libraries (PyTorch, TensorFlow, scikit-learn or equivalent) Linux OS Git/GitHub Willingness to learn: LLM tools, (vLLM, LangChain, etc.) CI/CD pipelines Docker/Singularity Diversity, Equity and Inclusiveness ESA is an equal opportunity employer, committed to achieving diversity within the workforce and creating an inclusive working environment. We therefore welcome applications from all qualified candidates irrespective of gender, sexual orientation, ethnicity, religious beliefs, age, disability or other characteristics. At the Agency we value diversity, and we welcome people with disabilities. Whenever possible, we seek to accommodate individuals with disabilities by providing the necessary support at the workplace. The Human Resources Department can also provide assistance during the recruitment process. If you would like to discuss this further, please contact us via email at contact.human.resources@esa.int. Important Information and DisclaimerDuring the recruitment process, the Agency may request applicants to undergo selection tests. Additionally, successful candidates will need to undergo basic screening before appointment, which will be conducted by an external background screening service, in compliance with the European Space Agency's security procedures. The information published on ESA’s careers website regarding working conditions is correct at the time of publication. It is not intended to be exhaustive and may not address all questions you would have. Nationality and Languages Please note that applications can only be considered from nationals of one of the following States: Austria, Belgium, Czechia, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Luxembourg, the Netherlands, Norway, Poland, Portugal, Romania, Slovenia, Spain, Sweden, Switzerland, and the United Kingdom. Nationals from Latvia, Lithuania and Slovakia as Associate Member States, or Canada as a Cooperating State, can apply as well as those from Bulgaria, Croatia, Cyprus and Malta as European Cooperating States (ECS). According to the ESA Convention, the recruitment of staff must take into account an adequate distribution of posts among nationals of the ESA Member States*. When short-listing for an interview, priority will be given to external candidates from under-represented Member States*. The working languages of the Agency are English and French. A good knowledge of one of these is required. Knowledge of another Member State language would be an asset. *Member States, Associate Members or Cooperating States.

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Responsibilities

You will develop AI models and integrate them into software applications to enhance the Agency's business processes. This includes working with structured and unstructured data, model development, testing, and communicating results to senior management.