Applied AI Scientist – Retrieval, RAG & LLM Workflows

Elsevier; Greater London; On-site; GBP 70,000 - 100,000; Full time

Benefits offered by this job

Home/office allowance

Generous vacation entitlement

Parental leave & family care

Job summary

Elsevier seeks a Data Scientist III to design, build, and evaluate advanced AI capabilities for LeapSpace and the Search & AI Platform. You will work with cross-functional teams on retrieval systems, generative AI, and evaluation frameworks to deliver production-ready AI-powered discovery tools used by researchers worldwide.

Applicants should have hands-on experience with NLP, information retrieval, and LLM-based applications, and be adept at turning cutting-edge AI techniques into scalable

Qualifications

• Bachelor's, Master's or PhD in Computer Science, Data Science, ML, NLP, Information Retrieval or related field.
• Experience in data science, machine learning, applied NLP, information retrieval, or generative AI.
• Hands-on with LLM-based applications and generative AI systems, RAG pipelines, and retrieval systems.
• Experience with lexical, vector, and hybrid search architectures.
• Knowledge of evaluation methodologies for IR and generative AI systems.
• Strong Python programming skills.
• Experience with PyTorch, Hugging Face, LangChain, LangGraph, Haystack.
• Experience with Databricks or equivalent distributed ML platforms.
• Understanding of experimentation methodologies and statistical analysis.
• Proficiency with data visualization tools (Tableau, Power BI, matplotlib, seaborn).

Responsibilities

• Develop and improve LLM-powered research workflows (QA, literature summarization, semantic discovery, citation-aware retrieval).
• Build agentic and multi-step AI workflows using LangGraph and orchestration tools.
• Apply NLP, generative AI, embeddings, and retrieval-augmented generation techniques.
• Evaluate AI models, tools, and frameworks; provide experimentation recommendations.
• Contribute to prompt engineering, grounding strategies, and hallucination mitigation.
• Integrate scientific metadata, ontologies, and knowledge assets into AI workflows.
• Design and optimize search and retrieval pipelines (lexical, vector, hybrid).
• Collaborate with teams to deploy and scale AI-powered solutions.
• Develop evaluation datasets, benchmarks, and annotation workflows.
• Conduct offline experiments and support online experimentation and A/B testing.

Skills

LLM-based apps

Generative AI

RAG pipelines

Retrieval systems

Search architectures

Evaluation methodologies

Python

PyTorch

Hugging Face

LangChain

LangGraph

Haystack

Databricks

Data visualization

Education

Bachelor's, Master's or PhD in Computer Science, Data Science, ML, NLP, or Information Retrieval

Tools

LangGraph

LangChain

PyTorch

Hugging Face

Haystack

Databricks

Tableau

Power BI

matplotlib

seaborn

Job description

Elsevier seeks a Data Scientist III to design, build, and evaluate advanced AI capabilities for LeapSpace and the Search & AI Platform. You will work with cross-functional teams on retrieval systems, generative AI, and evaluation frameworks to deliver production-ready AI-powered discovery tools used by researchers worldwide.

Applicants should have hands-on experience with NLP, information retrieval, and LLM-based applications, and be adept at turning cutting-edge AI techniques into scalable