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- Tasks: Design and implement cutting-edge NLP models to solve complex data challenges.
- Company: Join a dynamic AI team at a leading finance client.
- Benefits: Enjoy private healthcare, 28 days leave, and personal development budget.
- Why this job: Make a real impact by enhancing AI capabilities in a supportive environment.
- Qualifications: Experience with NLP frameworks and advanced Python skills required.
- Other info: Opportunity for career growth and innovation in a fast-paced setting.
The predicted salary is between 36000 - 60000 £ per year.
About the job
- Employment Type: Permanent
- Private healthcare and well-being programme
- 28 days annual leave plus bank holidays
- Enhanced parental leave policies
- Annual performance-based bonus
- Budget for personal development and certifications
About the Role:
Our finance client is seeking a talented Machine Learning Engineer NLP Specialist to join their dynamic AI team. You will play a key role in designing and implementing advanced Natural Language Processing (NLP) models, enabling smarter systems to improve search, information extraction, and classification. If you enjoy solving complex data challenges in an environment where innovation is encouraged, this role is for you.
Key Responsibilities:
- Design and implement state-of-the-art NLP models for tasks such as entity extraction, text summarisation, and semantic understanding.
- Process and analyse diverse datasets, including structured text, tables, and images, to extract meaningful insights.
- Develop indexing and retrieval systems for high-speed, accurate search functionality.
- Explore and implement advanced techniques, such as Retrieval-Augmented Generation (RAG), to enhance AI capabilities.
- Conduct experiments to measure and improve the performance of NLP models.
- Build custom language models tailored to specific industry requirements.
What We're Looking For:
- Proven experience with NLP frameworks such as Hugging Face, spaCy, or TensorFlow.
- Hands-on experience working with Large Language Models (LLMs) and deploying them in production.
- Advanced Python skills, with the ability to develop and optimise machine learning pipelines.
- Experience working with large, unstructured datasets and designing scalable workflows.
- Familiarity with Azure AI, AWS, or Google Cloud for AI deployment.
- Bonus: Knowledge of advanced NLP techniques and RAG.
Machine Learning Engineer NLP Specialist employer: Eliden
Contact Detail:
Eliden Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer NLP Specialist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your NLP projects, experiments, and any cool models you've built. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications come directly from passionate candidates. Plus, it shows you're genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Machine Learning Engineer NLP Specialist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with NLP frameworks and large language models. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about NLP and how you can contribute to our AI team. Keep it engaging and personal – we love to see your personality!
Showcase Your Projects: If you've worked on any cool NLP projects, make sure to mention them! Whether it's entity extraction or text summarisation, we want to know what you've done and how it relates to the role.
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 our team!
How to prepare for a job interview at Eliden
✨Know Your NLP Stuff
Make sure you brush up on your knowledge of NLP frameworks like Hugging Face and spaCy. Be ready to discuss your hands-on experience with Large Language Models and how you've deployed them in production. This is your chance to show off your technical skills!
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific data challenges you've faced and how you tackled them. Think of examples where you designed and implemented NLP models or improved their performance. Real-world examples will make you stand out!
✨Familiarise Yourself with Cloud Platforms
Since familiarity with Azure AI, AWS, or Google Cloud is a plus, do some homework on these platforms. Be ready to discuss how you've used them for AI deployment in past projects. It shows you're not just a coder but also understand the bigger picture.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company's AI team, their current projects, and future goals. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
