At a Glance
- Tasks: Conduct groundbreaking machine learning research and build large language models.
- Company: Pioneering AI research firm based in Greater London.
- Benefits: Flexible remote work, health benefits, and a weekly lunch stipend.
- Why this job: Join a team at the forefront of AI innovation and make a real impact.
- Qualifications: Currently pursuing a PhD in Machine Learning or NLP.
- Other info: Enjoy 6 weeks of paid time off and a dynamic research environment.
The predicted salary is between 500 - 1500 £ per month.
A pioneering AI research firm in Greater London is seeking a Research Intern to conduct cutting-edge machine learning research. This position involves building and training large language models, and working closely with a team to develop novel research ideas.
Suitable candidates will be pursuing a PhD in Machine Learning or NLP. Enjoy flexible remote options and various perks, including health benefits and a weekly lunch stipend.
AI Research Internship | Remote-Flexible + 6-Week PTO employer: Cohere Inc.
Contact Detail:
Cohere Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Research Internship | Remote-Flexible + 6-Week PTO
✨Tip Number 1
Network like a pro! Reach out to current or former interns and employees at the company. A friendly chat can give us insider info and might even lead to a referral.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your machine learning projects or research. This is your chance to impress them with what you can bring to the table.
✨Tip Number 3
Ace that interview! Research common interview questions for AI roles and practice your answers. We want to see you confident and ready to discuss your ideas and experiences.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace AI Research Internship | Remote-Flexible + 6-Week PTO
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in machine learning and NLP. We want to see how your skills align with the cutting-edge research we do, so don’t hold back on showcasing your projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re passionate about AI research and how your PhD journey has prepared you for this role. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Research Skills: In your application, include specific examples of your research work, especially any experience with building and training language models. We’re keen to know what innovative ideas you’ve explored and how they could contribute to our team.
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 Cohere Inc.
✨Know Your Stuff
Make sure you brush up on the latest trends in machine learning and NLP. Familiarise yourself with recent advancements and be ready to discuss how they relate to your own research. This shows your passion and commitment to the field.
✨Showcase Your Projects
Prepare to talk about any relevant projects you've worked on, especially those involving large language models. Be specific about your role, the challenges you faced, and the outcomes. This will help the interviewers see your practical experience in action.
✨Ask Thoughtful Questions
Come prepared with insightful questions about the company's research focus and future projects. This not only demonstrates your interest but also gives you a chance to assess if the company aligns with your career goals.
✨Be Yourself
While it's important to be professional, don't forget to let your personality shine through. The team is looking for someone who fits well with their culture, so being genuine can make a big difference in how you're perceived.