AI Scientist / Engineer – Speech Language ModelRole SummaryThe AI Scientist / Engineer – Speech Language Models leads the design, development, andevaluation of AI systems for language assessment, real‑time feedback, and skills evaluation.
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The rolefocuses on speech recognition, spoken language modeling, and automated scoring, ensuring modelsare 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:o AI‑driven speaking practice with instant feedback (learner‑facing).O Job‑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–basedapproaches. - Design experiments and conduct quantitative performance, reliability, and validity analyses toensure assessment quality and decision integrity. - Work across a range of speaking constructs such as interactional competence, pragmaticcompetence, 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 interactiveexperiences 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 ongoingquality and compliance for high‑stakes use cases. - Act as the technical lead for an AI conversational assessment product, partnering closely witha Product Manager to translate assessment goals, user needs, and business constraints intomodel and system design decisions. - Shape end‑to‑end conversational assessment design (task structure, prompts, turn‑taking,scoring logic, feedback timing) in collaboration with product and assessment stakeholders. - Balance assessment validity, user experience, system latency, and scalability when makingmodel and system design trade‑offs for production conversational assessments.Required Skills & Qualifications - Master’s or PhD in Computer Science, Electrical Engineering, Speech & Language Processing,Applied Linguistics, Language Assessment, or equivalent applied experience. - Hands‑on experience building speech recognition, spoken language understanding, orautomated scoring systems. - Strong programming skills in Python,



with experience using PyTorch or similar MLframeworks for speech and language modeling. - Solid grounding in machine learning, statistics, and experimental design, especially as appliedto model evaluation. - Experience with modern neural speech models and large language models, includingfine‑tuning and evaluation for spoken tasks. - Expertise in model evaluation metrics relevant to speech and assessment (accuracy, reliability,validity, fairness). - Familiarity with responsible AI practices, including bias analysis, interpretability, andgovernance for user‑impacting systems. - Strong communication skills, with the ability to explain model behavior and assessmentoutcomes to technical and non‑technical stakeholders. - Experience working in cross‑functional product teams, contributing to roadmap decisions,and shipping ML systems into production.Nice‑to‑Have / Domain Alignment - Experience with spoken feedback systems, pronunciation scoring, fluency analysis, orconversational AI. - Background in skills assessment, talent evaluation, or hiring platforms using AI‑baseddecision support. - Familiarity with human‑in‑the‑loop evaluation, rater alignment, or psychometric concepts forAI scoring systems.Impact of the RoleThis role directly enables: - Learner‑facing speaking practice with immediate, actionable feedback powered by speechLMs. - Hiring‑grade oral communication and skills assessments that support fair, data‑driven talentdecisions. xhfqzwm - Scalable, responsible speech AI systems that balance technical excellence with assessmentvalidity.Full timePosting Date:

📌 Lead Specialist, Ai Scientist (Madrid)
🏢 Pearson
📍 Madrid