Generative AI Data Scientist

TechYard; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

TechYard is seeking a highly capable Data Scientist to lead GenAI 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 GenAI hands-on experience, strong Python skills, and familiarity with OpenAI GPT-4 or similar models. You will collaborate with data engineers, MLOps, and product teams in a fast-paced environment.

Qualifications

• 5+ years of experience in Data Science / ML with GenAI focus.
• At least 1 year hands-on in LLM/GenAI projects.
• Strong Python and ML libraries experience.
• Experience with OpenAI GPT-4, Claude, or similar models.
• Knowledge of vector search and semantic search.
• Ability to deploy AI apps via APIs or web apps.

Responsibilities

• Design and build GenAI solutions using LLMs for business problems across domains.
• Fine-tune or adapt foundation models using domain data.
• Implement RAG pipelines, embedding models, and vector databases.
• Collaborate with data engineers, MLOps, and product teams to build end-to-end AI applications and APIs.
• Develop custom prompts and prompt chains using LangChain, LlamaIndex, PromptFlow, or similar frameworks.
• Evaluate model performance, mitigate bias, and optimize accuracy, latency, and cost.
• Stay up to date with trends in LLMs, transformers, and GenAI architecture.

Skills

Python

LLMs

LangChain

MLOps

Prompt tuning

Fine-tuning

Vector search

Cloud platforms

Communication

Tools

FAISS

Pinecone

ChromaDB

FastAPI

Streamlit

Flask

PyTorch

Job description

We are looking for a highly capable and innovative Data Scientist with experience in Generative AI to join our Data Science Team. You will lead the development and deployment of GenAI solutions, including LLM-based applications, prompt engineering, fine-tuning, embeddings, and retrieval-augmented generation (RAG) for enterprise use cases.

As part of your duties, you will be responsible for:

• Design and build Generative AI solutions using Large Language Models (LLMs) for business problems across domains like customer service, document automation, summarization, and knowledge retrieval.
• Fine-tune or adapt foundation models using domain-specific data.
• Implement RAG pipelines, embedding models, vector databases (e.g., FAISS, Pinecone, ChromaDB).
• Collaborate with data engineers, MLOps, and product teams to build end-to-end AI applications and APIs.
• Develop custom prompts and prompt chains using tools like LangChain, LlamaIndex, PromptFlow, or custom frameworks.
• Evaluate model performance, mitigate bias, and optimize accuracy, latency, and cost.
• Stay up to date with the latest trends in LLMs, transformers, and GenAI architecture.

Qualifications and experience we consider to be essential for the role:

• 5+ years of experience in Data Science / ML, with 1+ year hands‑on in LLMs / GenAI projects.
• Strong Python programming skills, especially in libraries such as Transformers, LangChain, scikit-learn, PyTorch, or TensorFlow.
• Experience with OpenAI (GPT-4), Claude, Mistral, LLaMA, or similar models.
• Knowledge of vector search, embedding models (e.g., BERT, Sentence Transformers), and semantic search techniques.
• Ability to build scalable AI workflows and deploy them via APIs or web apps (e.g., FastAPI, Streamlit, Flask).
• Familiarity with cloud platforms (AWS/GCP/Azure) and MLOps best practices.
• Excellent communication skills with the ability to translate technical solutions into business impact.

Skills and Personal attributes we would like to have:

• Experience with prompt tuning, few-shot learning, or LoRA-based fine-tuning.
• Knowledge of data privacy and security considerations in GenAI applications.
• Familiarity with enterprise architecture, SDLC, or building GenAI use cases in regulated domains (e.g., finance, insurance, healthcare).