AI Language Engineer, Cresta

• Bachelor’s or Master’s degree in Computer Science, Computational Linguistics, AI, Machine Learning, Linguistics, Cognitive Science, or a related field
• Demonstrated experience applying NLP concepts and techniques (classification, entity extraction, semantic analysis, summarization, prompting, RAG)
• Strong programming skills in Python with familiarity in NLP/AI frameworks (e.g., Hugging Face Transformers, TensorFlow, PyTorch)
• Experience with data preprocessing, model evaluation, and language dataset design
• Excellent analytical skills and ability to diagnose and communicate model behavior, linguistic patterns, and performance trade-offs
• Strong collaboration and communication skills across technical and non-technical stakeholders

Desirable

• We are seeking a versatile AI Language Engineer to design, build, and enhance natural language systems that power intelligent products and experiences, spanning both text and speech domains
• This role combines linguistic insight, applied NLP expertise, and AI engineering execution to advance language understanding, generation, and evaluation across real-world applications
• The AI Language Engineer will collaborate with product and engineering teams to translate language challenges into scalable AI solutions
• Design, develop, and refine large language model (LLM) workflows, including context engineering, prompt design, and evaluation frameworks to steer and improve model behaviors
• 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) workflows and evaluation frameworks, bridging audio-feature/signal-level processing with LLM-driven reasoning and orchestration
• Fine-tune and evaluate models using quantitative and qualitative metrics to ensure robust performance across tasks
• Analyze model outputs and conversational data to identify patterns, gaps, and failure modes, translating findings into actionable improvements
• Define and apply linguistic evaluation criteria to ensure tone, clarity, intent understanding, and contextual accuracy
• Experiment with prompt structures, retrieval strategies, and linguistic patterns to improve accuracy and robustness
• Drive R&D-style exploration on cutting-edge speech and language systems where best practices are still emerging, rapidly prototyping novel approaches and validating them through rigorous experimentation
• Lead data preprocessing, annotation, and language dataset creation, building reliable training and evaluation corpora
• Design experiments to test model adaptations and new techniques, tracking performance and iterating based on data insights
• Collaborate with software developers to integrate language models into production systems and ensure scalable deployment
• Build tooling for model evaluation, monitoring, and continuous improvement pipelines
• Extend evaluation and monitoring tooling to support large-scale, automated speech quality measurement for TTS and ASR in offline tests and production
• Support performance optimization, model serving architecture, and infrastructure integration
• Partner with product managers, conversation designers, UX researchers, and stakeholders to connect language capabilities with business objectives
• Serve as the NLP & language subject-matter expert within multidisciplinary teams
• Document methodologies, evaluation findings, best practices, and language guidelines to promote shared knowledge and reproducible workflows
• Present results and recommendations clearly to internal and external stakeholders