NLP Research Scientist

Years of Experience 3–6 years of applied NLP research experience (industry or academic).
Experience in a localization or multilingual NLP context is a strong plus.

 Design and execute research investigations across NLP topics:
automatic post-editing (APE), automated LQA, terminology extraction
and discovery, and LLM-based quality metrics.
 Evaluate large language models (GPT-4o, Claude, open-source models)
for localization tasks— measuring quality, cost, and latency trade-offs.
 Produce clear research conclusions delivered as User Stories (We have
decided. We
 define) that engineering teams can act on directly.
 Present research findings at sprint review sessions, communicating
results and
recommendations to both technical and non-technical stakeholders.
 Collaborate with engineers to validate that implemented solutions
match research findings; support post-deployment analysis.
 Investigate cost-efficiency improvements: prompt optimization, token
reduction strategies, non-LLM alternatives where appropriate.
 Stay current with NLP and LLM literature and evaluate applicability to
Lionbridge &
localization use cases.