Our Holy Grail at NLP is to enable computers achieve human-like comprehension of texts/languages. To get through our Challenges we don't just value differences, we seek them out. We invite them in.
One of our objectives is to further develop DeepPavlov Library — can open-source library of pretrained NLP models that has over 6K stars on GitHub and hundreds of customers worldwide. At the moment the DeepPavlov Library team is focused on building cutting-edge multilingual NLP models. Directions include, but are not limited to:
- Building groundbreaking multi-entity Named-Entity Recognition models capable of recognising over 30 types of entities
- Fine-tuning aspect-based Sentiment Analysis models
- Building multilingual Question Answering models
You can try out some of our models at DeepPavlov Demo page.
The Dialog Flow Framework (DFF) stands as a testament to our commitment to revolutionize the landscape of open-source dialogue systems. As part of our continuous efforts, we present open tasks for DFF, a cutting-edge, lightweight, open-source framework designed to empower developers in building sophisticated dialog systems driven by state-of-the-art machine learning models. Implementation of models, open-source development tasks:
- Development of a modern framework for creating dialogue systems based on machine learning models
- Document creation systems (analysis, reports, legal materials, etc.) based on templates and structured/unstructured data sources
- Development of non-trivial pipelines and their optimization for RAG systems
- Data structuring systems based on unstructured sources
- Processing complex queries in systems with logical reasoning and resolution of connections between data sources
You will have the opportunity to:
- Contribute to our Natural Language Processing stack
- Experiment with, apply, and benchmark new algorithms
- Learn to productize cutting-edge research
- Work in a high-growth, dynamic and worldwide project
- You have a background in/you are studying computer science, linguistics, or a related field
- You followed courses in machine learning, either online or during your bachelor/master.
- You having provable machine learning experience is a strong plus (E.g., private projects)
- You get to learn something
- External announcement of your work, prepare a paper
- Potential future employment opportunity at DeepPavlov.a
- 20 Weekly Hours
- 2-3 Month
- Unpaid
- Remote
