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- Tasks: Design and develop innovative generative AI methodologies to tackle complex challenges.
- Company: Join DeepMind, a leader in AI research with a collaborative culture.
- Benefits: Competitive salary, inclusive workplace, and opportunities for professional growth.
- Other info: Work in a dynamic environment with excellent career advancement opportunities.
- Why this job: Make a real impact in AI while collaborating with top experts in the field.
- Qualifications: PhD in Computer Science or related field, with experience in deep learning and ML frameworks.
The predicted salary is between 60000 - 80000 £ per year.
Minimum qualifications:
- PhD in Computer Science, a related field, or equivalent practical experience.
- Publication record in machine learning conferences or journals (e.g., NeurIPS, ICML, ICLR, KDD, AAAI).
- Experience in advanced deep learning, with specific experience in foundational or practical contributions to diffusion models.
- Experience with relevant ML frameworks such as JAX, TensorFlow, or PyTorch.
Preferred qualifications:
- Passion for AI and a collaborative, open‑minded approach to problem‑solving.
About The Job:
Our mission is to design and develop novel generative methodologies from the ground up, deploying them to solve some of the most complex challenges across two distinct domains: media models and groundbreaking scientific discovery. In this role, you will actively collaborate with our colleagues in Amsterdam, including regular on‑site visits. Serving as a critical bridge between core machine learning research and applied domains, you will utilize advanced diffusion techniques and novel generative methods to address ambitious problems in both media synthesis and science.
Responsibilities:
- Design, deploy, and accelerate generative models leveraging techniques like distillation to solve specific, high‑complexity challenges.
- Maintain a flexible, problem‑focused approach to research, identifying and utilizing the most effective algorithmic tools to overcome concrete technical roadblocks.
- Evaluate the datasets, training methodologies, and final outputs required to push the performance of large‑scale, domain‑specific generative models.
- Report developments and share deep scientific insights efficiently both verbally and in writing, mentoring peers and elevating the team’s overall technical capability.
Research Scientist, Generative AI, DeepMind in London employer: Google DeepMind
Contact Detail:
Google DeepMind Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Scientist, Generative AI, DeepMind in London
✨Tip Number 1
Network like a pro! Reach out to folks in your field, especially those at DeepMind or similar companies. Attend conferences, join online forums, and don’t be shy about sliding into DMs on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your research, projects, and any publications. Make it easy for potential employers to see what you can bring to the table. If you’ve got experience with JAX, TensorFlow, or PyTorch, highlight that!
✨Tip Number 3
Prepare for interviews by brushing up on your problem-solving skills. Be ready to discuss your approach to complex challenges, especially in generative AI. Practice explaining your thought process clearly and confidently – it’s all about showing how you tackle tough problems.
✨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 are proactive and engaged. So, get your application in and let’s make some waves in the AI world together!
We think you need these skills to ace Research Scientist, Generative AI, DeepMind in London
Some tips for your application 🫡
Show Off Your Research: Make sure to highlight your publication record in machine learning conferences or journals. We want to see your contributions to the field, so don’t hold back on showcasing your best work!
Tailor Your Application: When applying, tailor your CV and cover letter to reflect the specific qualifications mentioned in the job description. We love seeing how your experience aligns with our mission and the role's responsibilities.
Be Passionate About AI: Let your passion for AI shine through in your application. We’re looking for candidates who are not just qualified but also genuinely excited about solving complex challenges in generative methodologies.
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 the role. Plus, it’s super easy to do!
How to prepare for a job interview at Google DeepMind
✨Know Your Research Inside Out
Make sure you can discuss your PhD work and any publications in detail. Be prepared to explain your contributions to machine learning conferences and how they relate to generative AI. This shows your depth of knowledge and passion for the field.
✨Showcase Your Technical Skills
Familiarise yourself with the ML frameworks mentioned in the job description, like JAX, TensorFlow, or PyTorch. Be ready to discuss specific projects where you've used these tools, especially in relation to diffusion models. Practical examples will make your experience stand out.
✨Emphasise Collaboration and Problem-Solving
Highlight your collaborative experiences and how you approach problem-solving. Share examples of how you've worked with others to tackle complex challenges, as this role requires a flexible and open-minded approach to research.
✨Prepare for Technical Questions
Expect technical questions that assess your understanding of generative methodologies and advanced deep learning techniques. Brush up on key concepts and be ready to discuss how you would apply them to real-world problems, particularly in media synthesis and scientific discovery.