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Mecka AI is building the data infrastructure layer for robotics and embodied AI, designing and operating global systems for data capture, labeling, and hardware-enabled workflows used by leading AI labs and robotics companies to train and validate humanoid and embodied AI systems.
In this Research Scientist role, you will architect and train proprietary 3D reconstruction pipelines from scratch, transforming Mecka's continuous stream of high-quality, real-world multi-modal data into highly accurate, photorealistic digital environments. You will work on advanced neural reconstruction techniques such as 3D Gaussian Splatting and NeRFs, scale these models across multi-GPU clusters to handle massive spatial datasets, and integrate reconstructed environments to improve other segments of the perception pipeline.
Key responsibilities include:
- Designing, training, and scaling state-of-the-art models for dense 3D geometry extraction across multi-GPU clusters
- Reconstructing high-fidelity, physically accurate digital twins of real-world environments to provide spatial priors that improve downstream robotics pipelines and sim-to-real training
- Compressing, optimizing, and packaging massive 3D scene representations for high-framerate rendering in client-facing viewers
- Rapidly prototyping new architectures to isolate dynamic actors from static environments, resolve algorithmic bottlenecks, and integrate novel hardware sensor integrations
You will have access to proprietary spatial and temporal ground-truth data at scale, and your work will directly impact how the next generation of embodied AI agents bridge the gap between simulation and the physical world.
REQUIREMENTS:
- Deep expertise in 3D Computer Vision, Neural Rendering, multi-view geometry, and spatial modeling
- Proven experience training and scaling large-scale 3D vision models from scratch using PyTorch and multi-terabyte datasets
- Experience writing custom CUDA kernels to accelerate 3D operations, ray marching, or rasterization
Strong signals (preferred):
- First-author publications in top-tier venues (CVPR, ICCV, ECCV) focusing on 3D deep learning, neural rendering, or spatial transformers
- Specific projects deploying 3D assets to WebGL, custom rendering engines, or optimizing splats for interactive viewing that are publicly available
