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The NLP Specialist will play a key role in designing, improving, and evaluating Natural Language Processing (NLP) solutions across a variety of use cases, including Intent Detection, Summarization, Knowledge Retrieval, and Generative AI. This role partners closely with Data Scientists, ML Engineers, Conversation Designers, and Product teams to shape language strategies, improve model performance, and ensure high-quality user experiences. The ideal candidate brings strong linguistic intuition, applied NLP knowledge, and a passion for building intelligent, customer-facing AI systems.
Job Responsibility:
Analyze and improve NLP model behavior across tasks such as intent classification, entity extraction, summarization, and generative responses
Evaluate model outputs, identify gaps or failure modes, and propose data, prompt, or architectural improvements
Support experimentation with prompts, retrieval strategies, and language patterns to improve accuracy and robustness
Partner with product and engineering teams to translate business requirements into effective NLP solutions
Help prioritize NLP improvements and experiments based on customer impact, model performance, and strategic goals
Work cross-functionally with ML engineers, data scientists, conversation designers, and product managers to align on NLP requirements and delivery
Act as a language and NLP subject-matter expert within project teams
Define and apply qualitative and quantitative evaluation criteria for NLP outputs
Review model responses for linguistic quality, correctness, tone, and consistency, and drive iteration based on findings
Participate in customer-facing discussions to understand real-world language use, edge cases, and expectations
Translate customer feedback into actionable NLP improvements
Document NLP approaches, best practices, evaluation findings, and language guidelines to ensure scalability and consistency
Share insights and recommendations with internal stakeholders to raise overall NLP maturity
Stay current with emerging NLP and Generative AI trends, techniques, and tooling
Proactively suggest improvements to NLP workflows, evaluation methods, and model interaction strategies
Requirements:
Strong understanding of NLP concepts such as intent detection, entity recognition, retrieval-augmented generation, summarization, and prompt engineering
Experience working with or alongside ML models in production or near-production environments
Strong analytical thinking with an ability to diagnose model behavior and language patterns
Excellent command of written language and sensitivity to tone, clarity, and user intent
Proven ability to work effectively in cross-functional teams
Clear verbal and written communication skills to explain NLP decisions, tradeoffs, and recommendations
Familiarity with NLP tooling, model evaluation workflows, or AI platforms, with a willingness to learn new tools and frameworks
Nice to have:
Multilingual Proficiency: Strong ability to work with non-English languages (e.g., Spanish, French, German) and understand linguistic nuances across locales
Prompting, Copywriting & Regex: Strong prompt-writing skills for LLMs, understanding of customer-facing copy best practices, and comfort using regular expressions to support NLP improvements
Contact Center Experience: Familiarity with contact center environments and common conversational AI challenges