At a Glance
- Tasks: Lead the development of advanced AI models in NLP and genomics.
- Company: Join the University of Edinburgh, a leader in innovative research.
- Benefits: Enjoy flexible working, competitive salary, generous holidays, and a pension scheme.
- Other info: Flexible hybrid/remote options available for a dynamic work-life balance.
- Why this job: Make a real impact in biological sciences with cutting-edge AI technology.
- Qualifications: Experience in machine learning and a passion for AI applications.
The predicted salary is between 39347 - 46974 £ per year.
The University of Edinburgh is seeking a dynamic Machine Learning Engineer to lead the development of advanced AI models. You'll create and deploy tools that leverage NLP and generative AI, driving breakthroughs in biological sciences.
This full-time position offers flexible working options, a competitive salary of £39,347 - £46,974, and comprehensive staff benefits such as generous holidays and a defined benefits pension scheme.
ML Engineer — NLP & Genomics (Hybrid/Remote Options) employer: The University of Edinburgh
The University of Edinburgh is an exceptional employer, offering a vibrant work culture that fosters innovation and collaboration in the field of AI and biological sciences. With flexible working options, competitive salaries, and comprehensive benefits including generous holidays and a defined benefits pension scheme, employees are supported in their professional growth and well-being. Join us to be part of a prestigious institution that values your contributions and encourages meaningful advancements in research.
Contact Details:
The University of Edinburgh Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land ML Engineer — NLP & Genomics (Hybrid/Remote Options)
✨Tip Number 1
Network like a pro! Reach out to professionals in the AI and genomics fields on LinkedIn. Join relevant groups and engage in discussions to get your name out there.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects in NLP and generative AI. 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. Be ready to discuss your experience with machine learning models and how you've applied them in real-world scenarios.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who take the initiative to connect directly with us. It shows you're serious about landing that ML Engineer role!
We think you need these skills to ace ML Engineer — NLP & Genomics (Hybrid/Remote Options)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with NLP and generative AI. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI in biological sciences and how you can contribute to our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Projects:If you've worked on any cool projects related to machine learning, especially in NLP or genomics, make sure to mention them. We’re keen to see practical examples of your work that demonstrate your expertise and creativity.
Apply Through Our Website:We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at The University of Edinburgh
✨Know Your NLP and Genomics
Make sure you brush up on your knowledge of natural language processing and genomics. Be ready to discuss specific projects or models you've worked on in these areas, as well as the latest trends and technologies. This will show your passion and expertise.
✨Showcase Your Problem-Solving Skills
Prepare to discuss how you've tackled complex problems in previous roles. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This will help you clearly demonstrate your thought process and the impact of your work.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the team, the projects you'll be working on, and the company's vision for AI in biological sciences. This shows your genuine interest and helps you assess if it's the right fit for you.
✨Be Ready for Technical Challenges
Expect some technical questions or challenges during the interview. Brush up on your coding skills and be prepared to solve problems on the spot. Practising with mock interviews can help you feel more confident and ready to tackle these challenges.
