Job Description

Job Description
Seeking a Natural Language Processing Specialist to design, develop and optimize large language model (LLM) and speech system workflows, with the goal of improving performance, accuracy and applicability in language and audio tasks.
Responsibilities:
Design, develop and refine LLM workflows, including context engineering, design cues and evaluation frameworks to direct and improve model behavior.
Build language processing components for features such as intent detection, entity recognition, summarization, retrieval augmented generation (RAG), and conversational response quality.
Develop speech-to-text (ASR) and text-to-speech (TTS) evaluation frameworks and workflows, connecting audio feature processing with LLM-driven reasoning.
Tune and evaluate models using quantitative and qualitative metrics to ensure consistent performance across tasks.
Analyze model outputs and conversational data to identify patterns, gaps and failure modes, translating findings into practical improvements.
Define and apply linguistic evaluation criteria to ensure tone, clarity, understanding of intent, and contextual accuracy.
Experiment with cue structures, retrieval strategies, and linguistic patterns to improve accuracy and robustness.
Explore innovations in cutting-edge speech and language systems, prototyping novel approaches and validating them through rigorous experimentation.
Oversee data preprocessing, annotation and creation of language datasets, building reliable training and evaluation corpora.
Design experiments to test model adaptations and new techniques, tracking performance and iterating based on data analyses.
Collaborate with software developers to integrate language models into production systems and ensure scalable deployment.
Support performance optimization, model service architecture, and infrastructure integration.
Work with product managers, conversation designers, UX researchers, and stakeholders to connect language capabilities to business objectives.
Act as a specialist in NLP and language within multidisciplinary teams.
Document methodologies, evaluation findings, practices, and language guidelines to promote shared knowledge and reproducible workflows.
Present results and recommendations clearly to internal and external stakeholders.
Requirements:
Bachelor's or Master's degree in Computer Science, Computational Linguistics, AI, Machine Learning, Linguistics, Cognitive Sciences or a related field.
Experience in applying NLP concepts and techniques (classification, entity extraction, semantic analysis, summarization, hinting, RAG).
Python programming skills with familiarity with NLP/AI frameworks (e.g. Hugging Face Transformers, TensorFlow, PyTorch).
Experience with data preprocessing, model evaluation, and linguistic data set design.
Ability to diagnose and communicate model behavior, linguistic patterns, and performance trade-offs.
Collaboration and communication skills with technical and non-technical stakeholders.

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