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About the Role

Design, build, and evaluate advanced AI capabilities powering LeapSpace, focusing on applied AI research and development, prototyping intelligent workflows, integrating large language models with scientific data, and advancing AI-assisted research experiences.

Responsibilities

• Lead prototyping and development of LLM-powered research workflows, including scientific question answering, literature summarization, semantic exploration and discovery, research insight generation, and citation-aware reasoning.
• Design and iterate on agentic and multi-step AI workflows using frameworks such as LangGraph and related orchestration tooling.
• Apply state-of-the-art techniques in NLP, Generative AI, Embeddings and semantic representations, Retrieval-Augmented Generation (RAG), AI reasoning and orchestration.
• Rapidly evaluate emerging AI models, tooling, and frameworks to identify opportunities for product innovation.
• Translate applied AI research into scalable, production-oriented solutions that improve researcher productivity and trust.
• Contribute to experimentation around prompt engineering, context management, grounding strategies, and hallucination mitigation.
• Support integration of scientific metadata, ontologies, and knowledge assets into AI workflows.
• Design and optimize search and retrieval pipelines, including lexical, vector, and hybrid retrieval approaches.
• Develop and improve RAG systems that integrate LLMs with trusted scientific and biomedical content.
• Experiment with embeddings, re-ranking models, chunking strategies, and retrieval orchestration to improve relevance and answer quality.
• Build scalable workflows for semantic search and knowledge discovery.
• Collaborate closely with engineering teams to productionize AI and retrieval systems.
• Develop and evolve evaluation frameworks for search and AI systems, including IR metrics and LLM/RAG evaluation metrics.
• Design offline evaluation methodologies and contribute to online experimentation and A/B testing.
• Build and maintain evaluation datasets, benchmark suites, and annotation strategies.
• Drive rigorous experimentation to measure system improvements and user impact.
• Contribute to responsible AI practices, including quality, reliability, and trust evaluation.
• Partner with product managers, engineers, UX researchers, and domain experts to deliver impactful AI capabilities.
• Translate complex technical findings into actionable recommendations for stakeholders.
• Contribute to technical strategy and roadmap discussions for LeapSpace AI capabilities.

Requirements

• Master’s or PhD in Computer Science, Data Science, Machine Learning, NLP, Information Retrieval, or a related field
• Significant experience in applied AI, machine learning, NLP, or information retrieval
• Strong hands-on experience with LLM-based applications and generative AI systems
• Strong hands-on experience with RAG pipelines and retrieval systems
• Strong hands-on experience with search and retrieval architectures (lexical, vector, hybrid)
• Strong hands-on experience with evaluation methodologies for IR and generative AI systems
• Advanced programming skills in Python
• Experience with modern AI/ML frameworks and tooling (e.g., PyTorch, Hugging Face, LangChain, LangGraph, Haystack)
• Experience working with Databricks or similar distributed data/ML platforms
• Strong understanding of experimentation design, evaluation frameworks, and statistical analysis
• Proficiency with data visualization and analytical tooling (e.g., Tableau, Power BI, matplotlib, seaborn)
• Experience building AI assistants, agentic workflows, or conversational AI systems
• Experience working on large-scale search, ranking, or recommendation systems
• Familiarity with scientific, biomedical, or scholarly datasets
• Experience with knowledge graphs, ontologies, or semantic enrichment systems
• Exposure to production ML systems and MLOps practices
• Publications or applied research contributions in NLP, IR, search, or generative AI
• Experience building AI systems in regulated, high-trust, or content-rich domains

Skills

• Applied AI
• Machine Learning
• NLP
• Information Retrieval
• LLM-based applications
• Generative AI
• RAG pipelines
• Retrieval systems
• Search architectures
• Vector search
• Hybrid search
• Evaluation methodologies
• Python
• PyTorch
• Hugging Face
• LangChain
• LangGraph
• Haystack
• Databricks
• Experimentation design
• Statistical analysis
• Data visualization
• Analytical tooling
• AI assistants
• Agentic workflows
• Conversational AI
• Large-scale search
• Ranking systems
• Recommendation systems
• Scientific datasets
• Biomedical datasets
• Scholarly datasets
• Knowledge graphs
• Ontologies
• Semantic enrichment
• Production ML systems
• MLOps
• Prompt engineering
• Context management
• Grounding strategies
• Hallucination mitigation

Location

• USA

Work Type

• Flexible working hours

Experience Level

• Senior

Education Level

• Master's or PhD

Benefits

• Well-being initiatives
• Shared parental leave
• Study assistance
• Sabbaticals
• Flexible working hours
• Country specific benefits

About the Company

• Elsevier's mission is to help researchers, clinicians, and life sciences professionals advance discovery and improve health outcomes through trusted content, data, and analytics.
• The Platform Data Science organization develops foundational AI technologies that power experiences such as LeapSpace, Elsevier’s AI-powered research assistant, as well as Elsevier’s broader Search & AI Platform.
• As a global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society.
• Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education, and interactive learning, as well as exceptional healthcare and clinical practice.
• At Elsevier, your work contributes to the world’s grand challenges and a more sustainable future.
• We harness innovative technologies to support science and healthcare to partner for a better world.
• LexisNexis® Risk Solutions is part of RELX, a global provider of information and analytics for professional and business customers across industries.

Equal Opportunity

• We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.
• We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.