Entreprise:

Secteur: consulting / étude / stratégie
Taille: Moins de 20 employés
Binit Nearshore Services est une société de Conseil et de Services dans le domaine de l’IT et du BPO métiers . Anciennement MISC fondée en 2008, société de conseil dans le domaine du Supply Chain et de l’IT, l’activité de l’entreprise est étendue en 2020 et MISC est devenue BinitNS.
Nous conseillons nos clients Européens sur leur stratégie dans nos domaines d’expertise en intervenant pour leur compte en Europe sur place ou à distance. Quand ils le souhaitent, nous les accompagnons dans l’installation d’équipes de proximité (Nearshore) en Tunisie.
Description de l'annonce:
Binit Nearshore Services (BinitNS) is a Consulting and Services company operating in the ITO and BPO areas. We advise our European Customers for their IT projects: From Business Process Digitalization to Infrastructure evolutions and Cloud migrations.
One of our clients is a technology start-up providing data acquisition, analytics, and reporting solutions for investors and asset services.
In this context, we are hiring a Junior Machine Learning Engineer to contribute to the development and maintenance of a data science-driven document parsing stack. This is a unique opportunity to work in a dynamic, fast-paced startup environment applying advanced machine learning techniques such as Natural Language Processing (NLP), machine vision, and large language models (LLMs) within cloud-native architecture.
The ideal candidate is passionate about applied machine learning and eager to contribute to a production-grade AI system running on Kubernetes and serverless infrastructure.
Your Missions:
- Monitor and troubleshoot the data science stack running in production
- Investigate issues and propose solutions to improve reliability and accuracy
- Collaborate with product and client success teams to implement tactical improvements based on user feedback
- Contribute to the development of ML models for document parsing and information extraction
- Work on retrieval-augmented generation (RAG) pipelines and LLM-based architecture
- Participate in model evaluation and optimization for performance and scalability
Your Qualifications:
- An Engineering or Master’s degree in Data Science
- Strong proficiency in Python for machine learning, scripting, and automation
- Foundational understanding of machine learning, NLP, and computer vision concepts
- Exposure to cloud platforms (e.g., AWS), containers (e.g., Docker), and orchestration (e.g., Kubernetes) is a plus
- Curiosity, problem-solving mindset, and willingness to learn in a collaborative environment
- Excellent communication skills in English
What You Will Learn:
- Hands-on experience with cloud-native machine learning workflows
- Real-world application of NLP, LLMs, and visual language models in production
- Best practices in building reliable, scalable AI systems
- Collaboration with cross-functional international teams in a data-driven startup
Starting Date: As soon as
possible
Location: Tunisia
Perks: An amazing work environment and a highly competitive package