GenAI Data Scientist: LLMs, RAG & Prompting

GenAI Data Scientist: LLMs, RAG & Prompting

Full-Time 63000 - 77000 Β£ / year (est.) No working from home possible
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At a Glance

  • Tasks: Lead GenAI projects by designing and scaling LLM-based applications.
  • Company: Join TechYard, a forward-thinking company at the forefront of AI innovation.
  • Benefits: Enjoy competitive pay, flexible work options, and opportunities for professional growth.
  • Other info: Collaborative and fast-paced environment with great career advancement potential.
  • Why this job: Make a real impact in the AI space while working with cutting-edge technologies.
  • Qualifications: 5+ years in Data Science/ML, strong Python skills, and GenAI experience.

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

Tech Yard is seeking a highly capable Data Scientist to lead Gen AI initiatives.

You will design, deploy, and scale LLM-based applications, focusing on RAG, embeddings, and retrieval-augmented generation for enterprise use cases.

Ideal candidates have 5+ years in Data Science/ML with Gen AI hands-on experience, strong Python skills, and familiarity with Open AI GPT-4 or similar models.

You will collaborate with data engineers, MLOps, and product teams in a fast-paced environment.

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GenAI Data Scientist: LLMs, RAG & Prompting employer: TechYard

Join a dynamic consultancy that champions innovation in Data & AI transformation, where your expertise as a Senior Cloud Engineer will be valued and nurtured. With a strong emphasis on collaboration and professional growth, you'll have access to cutting-edge tools and technologies while working alongside industry leaders in a supportive environment. Located in a vibrant tech hub, this role offers unique opportunities to engage with enterprise clients and make a tangible impact on their AI initiatives.

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Contact Details:

TechYard Recruitment Team

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

Data Science
Machine Learning (ML)
Generative AI (GenAI)
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Embeddings
Python