At a Glance
- Tasks: Lead the development of advanced AI models in a vibrant academic environment.
- Company: Join the University of Edinburgh's innovative Learning Model of Life initiative.
- Benefits: Competitive salary, generous holiday, flexible work options, and comprehensive staff benefits.
- Other info: Dynamic team with opportunities for growth and collaboration across disciplines.
- Why this job: Make a real impact on healthcare by developing cutting-edge technologies in genetics.
- Qualifications: Degree in AI or related field, strong Python skills, and experience with NLP techniques.
The predicted salary is between 39347 - 46974 £ per year.
The Learning Model of Life is a cross-college initiative of The University of Edinburgh, supported by EPCC, the UK’s leading centre of Supercomputing and Data Science. We are seeking a dynamic and innovative Machine Learning Engineer to lead the development of advanced AI models. You'll be at the forefront of creating and deploying advanced tools that harness the power of NLP and generative AI to unlock new insights in biological sciences. This is a unique opportunity to have real impact by developing technologies that will drive the next wave of breakthroughs in genetics.
You will work in a vibrant academic environment at the University of Edinburgh, surrounded by experts in biology, medicine, computing, and machine learning. You'll have freedom to innovate, support to grow, and the opportunity to contribute to research that will transform the future of healthcare and beyond.
This post is full-time (35 hours per week); however, we are open to considering part-time or flexible working patterns. We are also open to considering requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular on-campus working.
Your Skills And Attributes For Success
- Relevant university degree in a relevant technical discipline (e.g., artificial intelligence, computer science, software engineering) or relevant post-degree professional experience.
- Strong Python development skills, with a good knowledge of existing packages for AI/NLP development.
- A very good knowledge of existing NLP techniques, LLMs and evaluation frameworks.
- Experience of training and/or fine-tuning custom AI/ML models.
- Evidence of having used git and associated tools for version control.
As a valued member of our team you can expect:
- A competitive salary of £39,347 - £46,974.
- An exciting, positive, creative, challenging and rewarding place to work.
- To be part of a diverse and vibrant international community.
- Comprehensive Staff Benefits, such as a generous holiday entitlement, a defined benefits pension scheme, staff discounts, family-friendly initiatives, and flexible work options.
Machine Learning Engineer employer: The University of Edinburgh
The Learning Model of Life at The University of Edinburgh offers an exceptional work environment for a Machine Learning Engineer, where innovation meets collaboration in a vibrant academic setting. With access to cutting-edge resources and a commitment to employee growth, you will be empowered to develop transformative AI technologies while enjoying comprehensive benefits, flexible working options, and the chance to make a significant impact in the field of biological sciences.
Contact Details:
The University of Edinburgh Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people 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 projects, especially those related to AI and NLP. This is your chance to demonstrate what you can do beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on common ML concepts and coding challenges. Practice explaining your thought process clearly, as communication is key in tech roles.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your relevant skills and experience in your application. We want to see your strong Python development skills and any experience you have with NLP techniques. Don’t hold back – this is your chance to shine!
Tailor Your Application:Take a moment to tailor your application to the specific role of Machine Learning Engineer. Mention how your background aligns with our mission at the University of Edinburgh and how you can contribute to the exciting projects we’re working on.
Be Clear and Concise:Keep your application clear and to the point. We appreciate well-structured applications that are easy to read. Use bullet points where necessary to make your key achievements stand out!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this fantastic opportunity. We can’t wait to hear from you!
How to prepare for a job interview at The University of Edinburgh
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and be ready to discuss the latest NLP techniques and LLMs. Familiarise yourself with the specific packages used in AI/NLP development, as you might be asked to demonstrate your knowledge or even solve a problem on the spot.
✨Showcase Your Projects
Prepare to talk about any relevant projects you've worked on, especially those involving training or fine-tuning AI/ML models. Bring examples that highlight your experience with version control tools like Git and GitHub, as this will show your practical skills and collaborative spirit.
✨Understand the Impact
Research how your role as a Machine Learning Engineer can contribute to breakthroughs in genetics and healthcare. Be ready to discuss how your work can unlock new insights in biological sciences, as this shows your passion for the field and aligns with the company's mission.
✨Be Open to Flexibility
Since the position offers flexible working patterns, be prepared to discuss your preferences for remote or hybrid work. This shows that you're adaptable and willing to find a working style that suits both you and the team.
