GenAI Data Scientist: LLMs, RAG & Embeddings Expert

GenAI Data Scientist: LLMs, RAG & Embeddings Expert

Full-Time 63000 - 77000 Β£ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Lead the development of cutting-edge GenAI solutions and work on LLM-based applications.
  • Company: Osmii, a forward-thinking tech company based in London.
  • Benefits: Flexible hybrid working, competitive salary, and opportunities for professional growth.
  • Other info: Collaborate with cross-functional teams in an innovative environment.
  • Why this job: Join a dynamic team and shape the future of AI technology.
  • Qualifications: Strong ML/NLP foundations and hands-on experience with GenAI frameworks.

The predicted salary is between 63000 - 77000 Β£ per year.

Osmii is seeking a Data Scientist in London with Gen AI expertise to lead the development and deployment of enterprise-grade Gen AI solutions.

You will work on LLM-based applications, prompt engineering, fine-tuning, embeddings, and retrieval-augmented generation (RAG).

Ideal candidates have strong ML/NLP foundations, hands-on Gen AI framework experience, and cloud environment familiarity.

This role supports flexible hybrid working in London and collaborates with cross-functional teams.

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GenAI Data Scientist: LLMs, RAG & Embeddings Expert employer: Osmii

Osmii is an exceptional employer that fosters a dynamic and innovative work culture, particularly for those passionate about GenAI and data science. With flexible hybrid working arrangements in London, employees enjoy a collaborative environment that encourages professional growth through cross-functional teamwork and cutting-edge projects. The company prioritises employee development, offering opportunities to enhance skills in LLMs, prompt engineering, and more, making it a rewarding place for aspiring data scientists.

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Contact Details:

Osmii Recruitment Team

We think you need these skills to ace GenAI Data Scientist: LLMs, RAG & Embeddings Expert

Python
SQL
Communication Skills
Problem-Solving Skills
Data Engineering
Automation
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