Natural Language Processing (NLP) Engineer

Your Personal AI
Cambridge
1 year ago
Applications closed

Related Jobs

View all jobs

Remote Principal NLP Research Scientist: Lead AI Innovation

Senior NLP & AI Research Scientist

NLP/LLM Research Scientist (PhD) – Cambridge Hybrid

Staff Machine Learning Scientist - AI Agent Systems

Postdoctoral Fellow in Computational Social Science & NLP

Senior AI Researcher & NLP Leader in Academia

Natural Language Processing (NLP) Engineer at Your Personal AI

Your Personal AI is seeking a talented Natural Language Processing (NLP) Engineer to join our AI Research and Development department. As an NLP Engineer, you will play a key role in developing cutting-edge algorithms and models to enhance our AI technology.

  • Collaborate with a team of researchers and developers to design and implement NLP solutions

  • Utilize machine learning techniques to improve language understanding and processing

  • Conduct experiments and analyze data to optimize NLP algorithms

  • Stay up-to-date with the latest advancements in NLP and AI technologies

If you are passionate about NLP and have a strong background in machine learning and data analysis, we would love to hear from you. Join us at Your Personal AI and be part of a dynamic team that is shaping the future of artificial intelligence.



Job Requirements for Natural Language Processing (NLP) Engineer at Your Personal AI

Thank you for your interest in the NLP Engineer role at Your Personal AI in the AI Research and Development department. To ensure we find the best candidate for this position, please review and include the following job requirements in your job posting:

  • Bachelor's degree in Computer Science, Engineering, or related field

  • Proven experience in developing NLP algorithms and models

  • Familiarity with machine learning techniques and frameworks

  • Proficiency in programming languages such as Python, Java, or C++

  • Strong analytical and problem-solving skills

  • Excellent communication and teamwork abilities

  • Ability to work independently and meet project deadlines

If the job requirements are not met, we kindly ask you to revise the job posting accordingly. Thank you for your attention to this matter.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.