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- Tasks: Design and develop cutting-edge 3D ML models and optimize them for production.
- Company: Join SpAItial, a trailblazer in AI and 3D technology, shaping the future of various industries.
- Benefits: Be part of a dynamic startup culture with opportunities for innovation and collaboration.
- Why this job: Make an impact in the AI revolution while working with passionate visionaries in a creative environment.
- Qualifications: PhD in Computer Science or related field with expertise in Machine Learning and 3D technologies required.
- Other info: We value diversity and inclusivity, welcoming applicants from all backgrounds.
The predicted salary is between 36000 - 60000 £ per year.
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SpAItial is pioneering the development of a frontier 3D foundation model, pushing the boundaries of AI, computer vision, and spatial computing. Our mission is to redefine how industries, from robotics and AR/VR to gaming and movies, generate and interact with 3D content.
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 our startup, you’ll be at the forefront of the AI revolution in 3D 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:
- Design and develop 3D foundational ML models
- Large-scale distributed model training
- Develop demos showcasing the trained model prototypes
- Processing and maintaining large data for model training
- Productionizing models, test-time model optimization
Qualifications:
- PhD in Computer Science or related field with a strong publication record in Machine Learning, Computer Vision, Robotics, or Graphics.
- Strong knowledge of 3D projective geometry
- Strong knowledge of modern 3D representations – 3D Gaussian Splatting, Neural Radiance Fields
- Experience in generative models (GANs, diffusion, LLMs, etc)
- Rich experience with large-scale 3D deep-learning in PyTorch
- Experience with modern video/image generative diffusion models
- Strong coding skills, able to rapidly iterate through ML experiments
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.
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Research Scientist employer: TN United Kingdom
Contact Detail:
TN United Kingdom Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Scientist
✨Tip Number 1
Familiarize yourself with the latest advancements in 3D foundational models and AI technologies. This will not only help you understand the company's mission better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Showcase your passion for innovation by discussing any personal projects or research that align with SpAItial's focus on 3D content generation. This demonstrates your proactive approach and commitment to pushing boundaries.
✨Tip Number 3
Network with professionals in the field of AI and 3D technology. Attend relevant conferences, webinars, or meetups to connect with like-minded individuals and potentially gain insights into the company culture at SpAItial.
✨Tip Number 4
Prepare to discuss your experience with large-scale distributed model training and generative models in detail. Be ready to share specific examples of challenges you've faced and how you overcame them, as this aligns with the responsibilities of the role.
We think you need these skills to ace Research Scientist
Some tips for your application 🫡
Understand the Company and Role: Dive deep into SpAItial's mission and values. Familiarize yourself with their work in 3D foundational models and how they intersect with AI, computer vision, and spatial computing. This understanding will help you tailor your application to align with their goals.
Highlight Relevant Experience: Make sure to emphasize your PhD and any relevant publications in Machine Learning, Computer Vision, or related fields. Discuss your experience with 3D projective geometry and modern 3D representations, as these are crucial for the role.
Showcase Your Skills: Detail your coding skills and experience with large-scale 3D deep-learning in PyTorch. Mention any projects involving generative models or video/image generative diffusion models to demonstrate your hands-on expertise.
Craft a Compelling Cover Letter: Write a cover letter that reflects your passion for pushing boundaries in technology. Share specific examples of how you've tackled complex problems and contributed to team goals, showcasing your alignment with SpAItial's collaborative culture.
How to prepare for a job interview at TN United Kingdom
✨Showcase Your Passion for 3D Technology
Make sure to express your enthusiasm for 3D technology and its applications in AI, computer vision, and spatial computing. Share specific examples of projects or research that demonstrate your commitment to pushing the boundaries in this field.
✨Highlight Relevant Experience
Discuss your experience with large-scale 3D deep learning, particularly in PyTorch. Be prepared to talk about your work with generative models and any relevant publications that showcase your expertise in machine learning and computer vision.
✨Demonstrate Problem-Solving Skills
Prepare to discuss complex problems you've tackled in your previous roles. SpAItial values individuals who are fearless in addressing challenges, so share how you approached these issues and the innovative solutions you implemented.
✨Emphasize Team Collaboration
Since teamwork is crucial at SpAItial, be ready to provide examples of how you've successfully collaborated with others in past projects. Highlight your ability to prioritize collective goals over personal ambition and how you contribute to a positive team environment.
