Overview
OBSERVABLE UNIVERSE
OF THE COMPANY
Our
customer is working on an advanced knowledge management system designed
specifically for organizations with large and diverse knowledge bases spread
across multiple sources of information. This system is capable of handling
structured, unstructured, and semi-structured data from different forms
(textual, graphical, video, and voice). This approach results in specific
challenges, one of them is text segmentation to be able deal with the more
kinds of textual data as regulatory, scientific and technical documentation.
As a
researcher, you will collaborate with the development team composed of backend,
frontend developers and UI/UX experts to take in charge the text segmentation
domain.
YOUR ROLE
Working
directly with lead developers and key stakeholders of the company, you will be in charge of the mastering of the text segmentation part of
the LLM,meaning :
• Collaborate with stakeholders
(co-founders, software developers, power users) to… understand the specific
needs for text segmentation.
• Choose appropriate algorithms
for different sort of text segmentation (readability, data analysis, or
feeding into further NLP processes). This might involve rule-based
methods, machine learning models, or a combination of both.
• Develop or adapt existing
algorithms for the specific nature of the text being processed (e.g.,
technical documents, legal documents etc.).
REQUIRED PROFILE
You
hold a PhD degree in Computer Science, Mathematics or a
related field with with thesis or post-doc experience and skills below :
• A strong
foundation in machine learning, natural language processing (NLP) and text
analytics is essential.
• Experience
with utilizing and fine-tuning large language models (LLM).
• Proficiency
in Python and data science/machine learning frameworks (like
PyTorch/Tensorflow, Transformers) is crucial.
• Hands-on
experience with NLP techniques and text analytics including text
normalization, tokenization, embedding generation.
• In-depth
knowledge of data mining techniques, especially those relevant to pattern
recognition, anomaly detection, and clustering in large datasets.
SOCIAL SPHERE
• Very good communication
skills in English.
• Used to work without
supervision.
• Motivated, curious,
disciplined and results oriented.
• Used to work within
international team.
SATELLITE
INFORMATION
Takeoff date : As soon as possible.
Rocket launch site : France but full remote.
Fuel : From 45 K€
Company:
Science me Up
Qualifications:
Language requirements:
Specific requirements:
Educational level:
Level of experience (years):
Senior (5+ years of experience)
