Dein persönlicher KI-Karriere-Agent
Research Engineer(m/w/x)
Designing generative 3D ML methods for physically-grounded 3D environment simulation. Expertise in diffusion models and transformers required. Equal opportunity employer.
Anforderungen
- 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
Aufgaben
- 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
Berufserfahrung
- ca. 1 - 4 Jahre
Ausbildung
- Bachelor-AbschlussODER
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- PyTorch
- deep learning
- generative models
- diffusion models
- transformers
- 3D processing
- camera geometry
- depth
- reconstruction
- point clouds
- meshes
- Gaussian splats
- ML systems
Benefits
Sonstige Vorteile
- Equal opportunity employer
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Research Engineer(m/w/x)
Designing generative 3D ML methods for physically-grounded 3D environment simulation. Expertise in diffusion models and transformers required. Equal opportunity employer.
Anforderungen
- 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
Aufgaben
- 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
Berufserfahrung
- ca. 1 - 4 Jahre
Ausbildung
- Bachelor-AbschlussODER
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- PyTorch
- deep learning
- generative models
- diffusion models
- transformers
- 3D processing
- camera geometry
- depth
- reconstruction
- point clouds
- meshes
- Gaussian splats
- ML systems
Benefits
Sonstige Vorteile
- Equal opportunity employer
Gefällt dir diese Stelle?
BetaDein Career Agent findet täglich ähnliche Jobs für dich.
Über das Unternehmen
SpAItial
Branche
Science
Beschreibung
The company is pioneering the development of a frontier 3D foundation model, pushing the boundaries of AI, computer vision, and spatial computing.
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