Job Description

Join the Impresso Project

The Impresso - Media Monitoring of the Past II project at the EPFL Digital Humanities Laboratory (DHLAB) is seeking a machine learning research engineer for the final phase of the project. The successful candidate will integrate into an active, collaborative development effort and contribute to the

application and consolidation of large-scale text mining pipelines for multilingual historical newspaper and radio archives

, bridging research, engineering, and digital humanities
About the project

Impresso is an interdisciplinary research project that brings together computational linguists, computer scientists, digital humanists, historians, and designers from EPFL, the University of Zurich, the University of Lausanne, and the CDH (Luxembourg), along with over 20 European partners. Funded by the Swiss National Science Foundation and the Luxembourg National Research Fund (2023-2027), the project pioneers new methods for exploring digitized newspaper and radio archives across languages, media, and borders through semantic enrichments and shared multilingual vector spaces

Mission

You will conduct applied research and engineering in natural language processing and text mining on large-scale, noisy, and multilingual historical texts. Working within an established and actively maintained codebase, you will help advance and consolidate the project's processing pipelines, bridging research and engineering in close collaboration with an interdisciplinary team.

Main duties and responsibilities

Apply and adapt existing NLP and computer vision models to large-scale, multilingual historical text and image data. Fine-tune or design models for additional text mining tasks, in particular media section classification. Support the creation of ground truth data by adapting the setup of web-based annotation tools, and assist in the management of annotation campaigns and data releases. Contribute to the maintenance and adaptation of web-serving setups for annotation models (TorchServe). Support the consolidation, validation, and documentation of existing data, pipeline components, and code modules. Additional activities (optional / depending on profile)
Collaborate on the design of Impresso WebApp, Datalab and API Participate in the development and adoption of standards for the representation and exchange of historical data (raw material and annotations) Contribute to scientific publications and project workshops on media mining, semantic indexing, and sustainability Your Profile
Experience: 1-3 years as a machine learning engineer or NLP researcher/programmer Education: MSc or PhD in NLP, Computer Science, Data Science, or a related field, or equivalent professional experience in machine learning/NLP Technical skills: + Solid expertise in machine learning, with practical experience in deep learning architectures (transformers, language models) and information extraction tasks
+ Proficiency in Python, Unix-based systems, databases (SQL/NoSQL), cloud storage and computing (S3, Kubernetes, Run:AI), and scripting/automation
+ Familiarity with collaborative development and code/model management platforms (GitHub, Hugging Face, and related tools)
Mindset: Curious, creative, rigorous, and attentive to detail; motivated by scientific research and cultural heritage applications, with a proactive and problem-solving attitude Strong sense of teamwork, communication, accountability, and production readiness Very good command of written and spoken English Desirable skills
Prior experience in an academic or research context Experience with historical or digitized documents and interdisciplinary collaboration Experience with image processing alongside text and language data is a plus Interest in student supervision and academic publication Knowledge of French or German

Practical details

Employment duration

: 12 months

Employment rate:

100%

Foreseen start of contract:

15.01.2026

Application deadline

: 8 December 2025

Interviews

: 15-18 December 2025

Salary

: according to EPFL salary scales and experience (typically between 80 and 95K CHF)

Place of work

: EPFL DHLAB, Lausanne, Switzerland

How to apply

: please upload your complete application (full CV, a 1-page cover letter and the contact information of 2 to 3 referees) via the EPFL portal *

Contact

: for any questions please contact Marina Buyrskaya Moyer (marina.butyrskayamoyer[at]epfl.ch) and Maud Ehrmann (maud.ehrmann[at]epfl.ch)