Senior/Lead NLP Engineer (LLM)

About us:
Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with the organization of the first Data Science UA conference, setting the foundation for our growth. Over the past 8 years, we have diligently fostered the largest Data Science Community in Eastern Europe.

About the role:
We are looking for a talented and passionate NLP Engineer (LLM) to join the team. In this role, you will be at the forefront of developing cutting-edge product using large language models (LLMs). This position is ideal for someone who has a deep understanding of deep learning, natural language processing (NLP), and has practical experience with LLMs.

Requirements:
- Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- Strong programming skills in Python, including experience with ML/NLP libraries (e.g., TensorFlow, PyTorch, Hugging Face Transformers).
- Knowledge of natural language processing techniques, including tokenization, stemming, lemmatization, and part-of-speech tagging.
- Hands-on experience with large language models and their applications.
- Experience with translation models including transformer models (BERT, GPT, T5, etc.), which are the backbone of modern LLMs.
- Excellent problem-solving abilities and a passion for innovation.
- Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Experience working in a fast-paced, startup environment.

Responsibilities:
- Fine-tune LLMs: Customize and optimize existing LLMs to fit the specific needs and improve performance.
- Research and Innovation: Stay abreast of the latest developments in LLMs, deep learning, and NLP. Propose and implement innovative approaches to solve complex problems.
- Collaboration: Work closely with the product and engineering teams to integrate machine learning models into the products and ensure they meet the high standards of scalability and reliability.

Published 19 March
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