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- Tasks: Architect and develop groundbreaking generative world models in AI and computer vision.
- Company: Join SpAItial, a leader in redefining 3D environments with innovative technology.
- Benefits: Be part of a dynamic team with opportunities for growth and impact in AI.
- Why this job: Shape the future of generative AI and tackle complex challenges with a talented team.
- Qualifications: PhD in Computer Science or related field with expertise in ML and generative models.
- Other info: We value diversity and inclusivity, welcoming applicants from all backgrounds.
The predicted salary is between 36000 - 60000 £ per year.
SpAItial is pioneering the next generation of World Models, pushing the boundaries of generative AI, computer vision, and the simulation of reality. We are moving beyond 2D pixels to build models that natively understand the physics and geometry of our world. Our mission is to redefine how industries, from robotics and AR/VR to gaming and cinema, generate and interact with physically-grounded 3D environments.
We’re looking for individuals who are bold, innovative, and driven by a passion for pushing the boundaries of what’s possible. You should thrive in an environment where creativity meets challenge and be fearless in tackling complex problems. Our team is built on a foundation of dedication and a shared commitment to excellence, so we value people who take immense pride in their work and place the collective goals of the team above personal ambition. As a part of SpAItial, you’ll be at the forefront of the AI revolution in generative AI technology, and we want you to be excited about shaping the future of this dynamic field. If you’re ready to make an impact, embrace the unknown, and collaborate with a talented group of visionaries, we want to hear from you.
Responsibilities
- Architect generative world models that reason about space, time, and physics.
- Design and develop image/video diffusion foundational ML models.
- Large-scale distributed model training on top of distributed cloud infra.
- Develop demos showcasing the trained model prototypes.
- Processing and maintaining large data for model training.
- Productionizing models, test-time model optimization.
Key Qualifications
- PhD in Computer Science or related field with a top-tier publication record in ML, Vision or graphics (CVPR, ECCV/ICCV, NeurIPS, SIGGRAPH, etc.).
- Strong knowledge of generative models such as image or video diffusion.
- Strong knowledge of cutting-edge architectures including diffusion transformers (DiT).
- Rich experience with deep learning frameworks such as PyTorch.
- Expert coding skills, and ability to rapidly iterate through ML experiments, including usage of modern AI coding tools.
At SpAItial, we are committed to creating a diverse and inclusive workplace. We welcome applications from people of all backgrounds, experiences, and perspectives. We are an equal opportunity employer and ensure all candidates are treated fairly throughout the recruitment process.
Research Scientist employer: spAItial AI
Contact Detail:
spAItial AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend events, and connect with current employees at SpAItial. A personal introduction can make all the difference when it comes to landing that interview.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects related to generative AI and computer vision. This gives us a tangible way to see your expertise and creativity in action.
✨Tip Number 3
Prepare for the unexpected! Be ready to tackle complex problems during interviews. Brush up on your problem-solving skills and think about how you can apply your knowledge of physics and geometry to real-world scenarios.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows us you’re genuinely interested in being part of the SpAItial team.
We think you need these skills to ace Research Scientist
Some tips for your application 🫡
Show Your Passion: When writing your application, let your enthusiasm for generative AI and computer vision shine through. We want to see that you're not just qualified, but genuinely excited about pushing the boundaries of what's possible in this field.
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with our mission at SpAItial. Focus on your PhD work, publications, and any projects that showcase your expertise in ML and generative models. We love seeing how your background fits into our vision!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re the perfect fit for our team. Share specific examples of your work, your problem-solving approach, and how you thrive in collaborative environments. We appreciate authenticity and creativity!
Apply Through Our Website: We encourage you to submit your application directly through our website. It’s the best way for us to receive your materials and ensures you’re considered for the role. Plus, it shows you’re keen on joining our innovative team at SpAItial!
How to prepare for a job interview at spAItial AI
✨Know Your Stuff
Make sure you brush up on the latest in generative AI, computer vision, and the specific technologies mentioned in the job description. Familiarise yourself with diffusion models and architectures like diffusion transformers. Being able to discuss these topics confidently will show your passion and expertise.
✨Showcase Your Work
Prepare to discuss your previous projects and publications, especially those related to ML and computer vision. Bring along examples of your work or demos that highlight your skills in developing models and handling large datasets. This will give the interviewers a tangible sense of what you can bring to the team.
✨Emphasise Team Spirit
SpAItial values collaboration and collective goals, so be ready to talk about how you've worked effectively in teams before. Share experiences where you put team success above personal ambition, and how you’ve contributed to a positive team environment.
✨Be Bold and Creative
Since the role requires innovation and tackling complex problems, don’t shy away from discussing your creative approaches to challenges. Think of examples where you pushed boundaries or came up with unique solutions in your past work. This will resonate well with their mission of redefining industries through creativity.
