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- Tasks: Lead innovative research in reinforcement learning and mentor junior scientists.
- Company: Global communications platform based in London with a diverse team.
- Benefits: Strong benefits, hybrid work schedule, and opportunities for professional growth.
- Why this job: Make a real impact by breaking down language barriers through cutting-edge research.
- Qualifications: PhD in a relevant field and over 5 years of ML research experience.
- Other info: Join a dynamic team committed to innovation and collaboration.
The predicted salary is between 48000 - 72000 £ per year.
A global communications platform in London seeks a Senior Staff Research Scientist to lead groundbreaking research in reinforcement learning. The ideal candidate will have a PhD in a relevant field and over 5 years of ML research experience. This position involves mentoring junior scientists, defining scientific direction, and building state-of-the-art learning pipelines. Join a diverse team with a commitment to breaking down language barriers while enjoying a hybrid work schedule with strong benefits.
Senior Staff Research Scientist – Foundation Models (Hybrid) in London employer: DeepL
Contact Detail:
DeepL Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Staff Research Scientist – Foundation Models (Hybrid) in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees on LinkedIn and ask about their experiences. A friendly chat can give you insider info and might even lead to a referral.
✨Tip Number 2
Prepare for the interview by brushing up on your reinforcement learning knowledge. Be ready to discuss your past projects and how they relate to the role. We want to see your passion and expertise shine through!
✨Tip Number 3
Show off your mentoring skills! Think of examples where you've guided junior scientists or collaborated with teams. This is key for a role that involves leadership and defining scientific direction.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace Senior Staff Research Scientist – Foundation Models (Hybrid) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in ML research and reinforcement learning. We want to see how your background aligns with the role, so don’t be shy about showcasing your PhD and any projects that demonstrate your expertise.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about leading research in this area and how you can contribute to our mission. We love seeing candidates who can articulate their vision and fit within our diverse team.
Showcase Your Mentoring Skills: Since mentoring junior scientists is part of the gig, share examples of how you've supported others in their research journeys. We appreciate candidates who can foster growth and collaboration within 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 get the best chance to showcase your skills to us!
How to prepare for a job interview at DeepL
✨Know Your Research Inside Out
Make sure you can discuss your past research projects in detail, especially those related to reinforcement learning. Be prepared to explain your methodologies, findings, and how they can apply to the role you're interviewing for.
✨Showcase Your Mentoring Skills
Since this role involves mentoring junior scientists, think of examples where you've successfully guided others. Be ready to share specific instances that highlight your leadership style and how you foster growth in your team.
✨Align with Their Vision
Research the company’s mission and values, particularly their commitment to breaking down language barriers. Prepare to discuss how your work aligns with their goals and how you can contribute to their scientific direction.
✨Prepare for Technical Questions
Expect in-depth technical questions about machine learning and reinforcement learning. Brush up on the latest advancements in the field and be ready to discuss how you would build state-of-the-art learning pipelines.
