SpAItial
Research Scientist - 3D Diffusion(m/w/x)
Full-timeOn-siteNot specified
München
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SPSpAItial
Research Engineer(m/w/x)
München
Full-timeOn-siteExperienced
AI/ML
Data Science
Nejo AI Summary
Designing generative 3D ML methods for physically-grounded 3D environment simulation. Expertise in diffusion models and transformers required. Equal opportunity employer.
Requirements
- Bachelor's or Master's degree, or equivalent project/research experience
- Degree in computer science, machine learning, computer vision, graphics, robotics, or related field
- Strong fundamentals in deep learning
- Strong fundamentals in generative models
- Expertise in diffusion models and transformers
- Solid understanding of 3D processing concepts
- Knowledge of camera geometry, depth, reconstruction, point clouds, meshes, or Gaussian splats
- Proficiency in Python
- Proficiency in deep learning frameworks
- Experience in model training and optimization
- Ability to implement research papers
- Ability to run experiments
- Ability to iterate quickly on new ideas
- Strong coding skills
- Passion for building reliable, scalable ML systems
Tasks
- Design generative 3D machine learning methods
- Develop cutting-edge generative 3D methods
- Create high-quality 3D content from inputs
- Build models for 3D reconstruction
- Train models for 3D reconstruction
- Optimize models for 3D reconstruction
- Evaluate models for 3D reconstruction
- Build models for novel view synthesis
- Train models for novel view synthesis
- Optimize models for novel view synthesis
- Evaluate models for novel view synthesis
- Build models for world generation
- Train models for world generation
- Optimize models for world generation
- Evaluate models for world generation
- Implement state-of-the-art 3D representations
- Experiment with point cloud representations
- Experiment with mesh representations
- Experiment with 3D Gaussian Splatting
- Develop training pipelines
- Develop loss functions
- Improve geometry accuracy
- Improve visual fidelity
- Improve consistency
- Integrate physics-aware priors
- Integrate world model capabilities
- Analyze model performance
- Debug model failure cases
- Iterate rapidly to improve quality
- Iterate rapidly to improve robustness
Work Experience
- approx. 1 - 4 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- PyTorch
- deep learning
- generative models
- diffusion models
- transformers
- 3D processing
- camera geometry
- depth
- reconstruction
- point clouds
- meshes
- Gaussian splats
- ML systems
Benefits
Other Benefits
- Equal opportunity employer
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of SpAItial and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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SPSpAItial
Research Engineer(m/w/x)
München
Full-timeOn-siteExperienced
AI/ML
Data Science
Nejo AI Summary
Designing generative 3D ML methods for physically-grounded 3D environment simulation. Expertise in diffusion models and transformers required. Equal opportunity employer.
Requirements
- Bachelor's or Master's degree, or equivalent project/research experience
- Degree in computer science, machine learning, computer vision, graphics, robotics, or related field
- Strong fundamentals in deep learning
- Strong fundamentals in generative models
- Expertise in diffusion models and transformers
- Solid understanding of 3D processing concepts
- Knowledge of camera geometry, depth, reconstruction, point clouds, meshes, or Gaussian splats
- Proficiency in Python
- Proficiency in deep learning frameworks
- Experience in model training and optimization
- Ability to implement research papers
- Ability to run experiments
- Ability to iterate quickly on new ideas
- Strong coding skills
- Passion for building reliable, scalable ML systems
Tasks
- Design generative 3D machine learning methods
- Develop cutting-edge generative 3D methods
- Create high-quality 3D content from inputs
- Build models for 3D reconstruction
- Train models for 3D reconstruction
- Optimize models for 3D reconstruction
- Evaluate models for 3D reconstruction
- Build models for novel view synthesis
- Train models for novel view synthesis
- Optimize models for novel view synthesis
- Evaluate models for novel view synthesis
- Build models for world generation
- Train models for world generation
- Optimize models for world generation
- Evaluate models for world generation
- Implement state-of-the-art 3D representations
- Experiment with point cloud representations
- Experiment with mesh representations
- Experiment with 3D Gaussian Splatting
- Develop training pipelines
- Develop loss functions
- Improve geometry accuracy
- Improve visual fidelity
- Improve consistency
- Integrate physics-aware priors
- Integrate world model capabilities
- Analyze model performance
- Debug model failure cases
- Iterate rapidly to improve quality
- Iterate rapidly to improve robustness
Work Experience
- approx. 1 - 4 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- PyTorch
- deep learning
- generative models
- diffusion models
- transformers
- 3D processing
- camera geometry
- depth
- reconstruction
- point clouds
- meshes
- Gaussian splats
- ML systems
Benefits
Other Benefits
- Equal opportunity employer
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of SpAItial and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
SpAItial
Industry
Science
Description
The company is pioneering the development of a frontier 3D foundation model, pushing the boundaries of AI, computer vision, and spatial computing.
Not a perfect match?
- SpAItial
Research Scientist - 3D Diffusion(m/w/x)
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Research Engineer Neural Reconstruction - New College Graduate(m/w/x)
Full-timeOn-siteExperiencedMünchen - SpAItial
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Full-timeOn-siteExperiencedMünchen