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- Tasks: Design and implement advanced NLP models to enhance AI capabilities.
- Company: Leading finance technology firm in Greater London with a focus on innovation.
- Benefits: Private healthcare, annual leave, and performance-based bonuses.
- Why this job: Join a cutting-edge team and work on innovative AI projects that make a difference.
- Qualifications: Experience with NLP frameworks, large language models, and Python required.
- Other info: Dynamic work environment with opportunities for professional growth.
The predicted salary is between 36000 - 60000 £ per year.
A leading finance technology firm in Greater London is seeking a Machine Learning Engineer NLP Specialist to design and implement advanced Natural Language Processing models. You will work on innovative projects to enhance AI capabilities while processing diverse datasets.
Ideal candidates have proven experience with NLP frameworks, large language models, and Python.
The position offers benefits including private healthcare, annual leave, and a performance-based bonus.
NLP ML Engineer: RAG & LLMs for Smart Search in London employer: Eliden
Contact Detail:
Eliden Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land NLP ML Engineer: RAG & LLMs for Smart Search in London
✨Tip Number 1
Network like a pro! Reach out to folks in the finance tech space, especially those working with NLP and ML. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your NLP projects or contributions to open-source. This gives us a tangible way to see what you can do beyond the usual application.
✨Tip Number 3
Prepare for the technical interview! Brush up on your Python skills and be ready to discuss your experience with NLP frameworks and large language models. We love seeing candidates who can think on their feet.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we’re always on the lookout for passionate individuals who want to make an impact in AI.
We think you need these skills to ace NLP ML Engineer: RAG & LLMs for Smart Search in London
Some tips for your application 🫡
Show Off Your NLP Skills: Make sure to highlight your experience with NLP frameworks and large language models in your application. We want to see how you've tackled similar projects and the impact you've made!
Be Specific About Your Experience: When detailing your past work, be specific about the datasets you've worked with and the results you've achieved. We love numbers and concrete examples that showcase your skills!
Tailor Your Application: Don’t just send a generic CV and cover letter. Tailor your application to reflect the job description. Mention how your background aligns with our innovative projects and the role's requirements.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Eliden
✨Know Your NLP Stuff
Make sure you brush up on your knowledge of Natural Language Processing frameworks and large language models. Be ready to discuss specific projects you've worked on, the challenges you faced, and how you overcame them. This will show your depth of understanding and practical experience.
✨Show Off Your Python Skills
Since Python is a key requirement for this role, be prepared to demonstrate your coding skills. You might be asked to solve a problem or explain your thought process while coding. Practise common algorithms and data structures in Python to ensure you're sharp and ready.
✨Understand the Company’s Vision
Research the finance technology firm and understand their products and services. Knowing how they leverage AI and NLP can help you tailor your answers and show that you're genuinely interested in contributing to their goals. It also gives you a chance to ask insightful questions.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions where you'll need to think on your feet. Prepare examples from your past experiences where you had to implement NLP solutions or work with diverse datasets. Use the STAR method (Situation, Task, Action, Result) to structure your responses clearly.
