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- Tasks: Architect generative world models and design foundational ML models.
- Company: Pioneering AI technology firm in Greater London with an inclusive culture.
- Benefits: Competitive salary, dynamic work environment, and opportunities for innovation.
- Why this job: Shape the future of AI and work on groundbreaking projects.
- Qualifications: PhD in Computer Science and expertise in generative models and deep learning.
- Other info: Join a dynamic team with a focus on collaboration and creativity.
The predicted salary is between 36000 - 60000 £ per year.
A pioneering AI technology firm in Greater London is seeking talented individuals to architect generative world models that understand physics and geometry.
Responsibilities include:
- Designing foundational ML models
- Distributed model training
- Showcasing prototype demos
The ideal candidate has a PhD in Computer Science with a strong publication record and deep knowledge of generative models and deep learning frameworks like PyTorch.
Join us to shape the future of AI in a dynamic and inclusive workplace.
Research Scientist - Generative World Models & 3D AI employer: spAItial AI
Contact Detail:
spAItial AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Scientist - Generative World Models & 3D AI
✨Tip Number 1
Network like a pro! Reach out to professionals in the AI field on LinkedIn or at industry events. A personal connection can often get your foot in the door faster than a CV.
✨Tip Number 2
Showcase your work! Create a portfolio of your projects, especially those related to generative models and deep learning. This gives potential employers a tangible sense of your skills and creativity.
✨Tip Number 3
Prepare for technical interviews by brushing up on your ML concepts and coding skills. Practice explaining your past research and how it relates to the role – clarity is key!
✨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 proactive about their job search.
We think you need these skills to ace Research Scientist - Generative World Models & 3D AI
Some tips for your application 🫡
Show Off Your Expertise: Make sure to highlight your PhD and any relevant publications in your application. We want to see your deep knowledge of generative models and frameworks like PyTorch, so don’t hold back!
Tailor Your Application: Customise your CV and cover letter to reflect the specific responsibilities mentioned in the job description. We love seeing how your experience aligns with designing ML models and distributed training.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that make it easy for us to see your qualifications and passion for AI.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for this exciting opportunity.
How to prepare for a job interview at spAItial AI
✨Know Your Stuff
Make sure you brush up on generative models and deep learning frameworks like PyTorch. Be ready to discuss your previous research and how it relates to the role. Having a solid grasp of physics and geometry will also help you stand out.
✨Showcase Your Work
Prepare to present your past projects or publications. Bring along examples that highlight your skills in designing ML models and any prototype demos you've worked on. This will give the interviewers a clear picture of your capabilities.
✨Ask Smart Questions
Think of insightful questions about the company's current projects or future directions in AI. This shows your genuine interest in the role and helps you gauge if the company is the right fit for you.
✨Be Yourself
While it's important to demonstrate your technical skills, don't forget to let your personality shine through. The company values a dynamic and inclusive workplace, so showing your enthusiasm and passion for AI can make a big difference.
