At a Glance
- Tasks: Design and improve NLP solutions for customer conversations using AI.
- Company: Join Cresta, a cutting-edge tech company born from Stanford's AI lab.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on continuous improvement and innovation.
- Why this job: Make a real impact by shaping intelligent AI systems that enhance customer experiences.
- Qualifications: Strong NLP knowledge, analytical skills, and experience with ML models.
The predicted salary is between 36000 - 60000 £ per year.
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 behavioural best practices, automate conversations and inefficient processes, and empower every team member to work smarter and faster.
About The Role
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 behaviour 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 & Prioritisation: Partner with product and engineering teams to translate business requirements into effective NLP solutions. Help prioritise 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
- NLP Expertise: Strong understanding of NLP concepts such as intent detection, entity recognition, retrieval-augmented generation, summarisation, 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 behaviour 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, trade-offs, 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 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.
We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta.ai domain. Any outreach claiming to be from Cresta via other sources should be ignored. If you are uncertain whether you have been contacted by an official Cresta employee, reach out to recruiting@cresta.ai.
NLP Specialist employer: Cresta
Cresta is an exceptional employer that fosters a collaborative and innovative work culture, where every team member is empowered to contribute to cutting-edge AI solutions in the contact centre space. With strong leadership from industry pioneers and a commitment to employee growth through continuous learning and development opportunities, Cresta offers a unique environment for NLP Specialists to thrive and make a meaningful impact on customer interactions. Located in a vibrant tech hub, employees benefit from a dynamic atmosphere that encourages creativity and professional advancement.
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We think this is how you could land NLP Specialist
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We think you need these skills to ace NLP Specialist
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Cresta. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Cresta
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
