Teams at Elsevier

Design, develop, and deploy ML, NLP, and generative-AI solutions (including LLMs and RAG) to improve search, retrieval, recommendation, and question-answering across scientific publications and datasets. Build scalable pipelines, evaluation frameworks, and production-quality Python code while collaborating with engineering, product, UX, and domain experts to measure and improve model reliability, relevance, and user impact.

Develop and execute automated functional and non-functional tests using JavaScript, TypeScript, Playwright, and Selenium. Build scalable test frameworks, perform primarily end-to-end and API testing, ensure appropriate feature coverage, and investigate production incidents. Collaborate with agile teams to support consistent, on-time delivery of high-quality software.

Develop and maintain Python data pipelines, automations, and customer-facing scientific data solutions supporting AI and NLP products. Collaborate with senior engineers and curation teams to build vocabularies, ontologies, and software that assists manual curation. Contribute to production-ready tools, cloud-based workflows, testing, code reviews, and cross-functional collaboration across Elsevier.