About Netropy AI

Netropy AI is a startup pioneering Physical AI and high-fidelity simulation solutions for industries such as autonomous driving and robotics. We leverage video-based 3D reconstruction, advanced computer vision, and generative technologies to bridge the gap between the virtual and physical worlds.

About the Role

We are looking for a Research Engineer to join our team and push the boundaries of Physical AI. In this role, you will combine cutting-edge research in generative AI and foundation models with image and 3D reconstruction. You will play a pivotal role in developing the next generation of simulation technology.

Key Responsibilities

• Innovate & Ideate: Generate, propose, and evaluate novel research ideas to drive the continuous evolution of our AI technology stack.
• Advanced Development: Develop and implement state-of-the-art 3D/4D reconstruction technologies, including Gaussian Splatting, Vision Generative Models, and Geometric Foundation Models.
• Data Engineering: Manage the lifecycle of large-scale datasets, including preprocessing and curation, to support robust model training and evaluation.
• Product Integration: Optimize research prototypes and integrate developed AI models into our core products, ensuring seamless performance and scalability.

Qualifications

Required (Must-Have)

To be considered for this role, applicants must meet the following criteria:

• Experience: 2+ years of research experience in Computer Vision, Computer Graphics, or related fields (Academic or Industrial).
• Generative AI Expertise: A deep understanding of Vision Generative and Foundation Models (e.g., Diffusion models, Transformers).
• Technical Foundation: Strong grasp of traditional computer vision and fundamental mathematics (Linear Algebra, Calculus, Statistics, and Probability).
• Deep Learning Proficiency: Extensive knowledge of Deep Learning literature with the ability to rapidly comprehend and implement new technologies.
• Mindset: Strong critical thinking skills, a hands-on approach to problem-solving, and the ability to learn quickly in a fast-paced environment.
• Communication: Professional proficiency in English for technical collaboration.

Preferred (Nice-to-Have)

• Specialized Research: Experience researching Vision Diffusion or Flow Matching models.
• Large-Scale Training: Hands-on experience training or fine-tuning Large Vision Models (LVMs) on multi-GPU setups.
• Publication Record: A track record of publishing research at top-tier conferences such as CVPR, SIGGRAPH, ICCV, NeurIPS, or ECCV.