NLP Specialist in London

Cresta is on a mission to turn every customer conversation into a competitive advantage by unlocking the true potential of the contact center. Our platform combines the best of AI and human intelligence to help contact centers discover customer insights and behavioral best practices, automate conversations and inefficient processes, and empower every team member to work smarter and faster.

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.

Responsibilities

• NLP Development & Analysis: 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.
• Use Case Design & Prioritization: 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.
• Collaboration: 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.
• Quality & Evaluation: 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.
• Customer & Stakeholder Engagement: Participate in customer-facing discussions to understand real-world language use, edge cases, and expectations. Translate customer feedback into actionable NLP improvements.
• Documentation & Knowledge Sharing: 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.
• Continuous Improvement: Stay current with emerging NLP and Generative AI trends, techniques, and tooling. Proactively suggest improvements to NLP workflows, evaluation methods, and model interaction strategies.

Qualifications We Value

• NLP Expertise: 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.
• Analytical & Linguistic Skills: 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.
• Collaboration & Communication: Proven ability to work effectively in cross-functional teams. Clear verbal and written communication skills to explain NLP decisions, tradeoffs, and recommendations.
• Tooling & Technical Comfort: Familiarity with NLP tooling, model evaluation workflows, or AI platforms, with a willingness to learn new tools and frameworks.
• Preferred Skills: 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.