Lead Specialist, AI Scientist

AI Scientist / Engineer – Speech Language Model Role Summary The AI Scientist / Engineer – Speech Language Models leads the design, development, and evaluation of AI systems for language assessment, real‑time feedback, and skills evaluation. The role focuses on speech recognition, spoken language modeling, and automated scoring, ensuring models are accurate, reliable, fair, and scalable across learner‑facing and hiring‑facing applications. Key Responsibilities Design, build, and improve speech language models for spoken response understanding, pronunciation analysis, fluency, prosody, and communicative effectiveness. Develop and evaluate automated scoring and feedback pipelines for speaking tasks used in: oAI‑driven speaking practice with instant feedback (learner‑facing). oJob‑relevant oral communication and soft‑skills assessments (hiring‑facing). Train, fine‑tune, and evaluate acoustic models, cascading models, speech-to-speech models, speech LMs, and scoring models, including neural and large language model–based approaches. Design experiments and conduct quantitative performance, reliability, and validity analyses to ensure assessment quality and decision integrity. Work across a range of speaking constructs such as interactional competence, pragmatic competence, spoken critical thinking skills etc. Perform detailed error analysis, intra- and inter-agent rater reliability studies on ASR outputs, spoken features, and scoring behaviors to guide model and product improvements. Collaborate with product, UX, and assessment scientists to integrate models into interactive experiences such as practice simulations, and hiring workflows. Apply responsible AI principles to speech systems, including fairness across accents, dialects, and proficiency levels, as well as transparency of feedback and scores. Support model monitoring and governance in production environments, ensuring ongoing quality and compliance for high‑stakes use cases. Act as the technical lead for an AI