Research Scientist - 3D Environment Reconstruction

Kindredventures; Toronto; Sur place; CAD 120 000 - 180 000; Plein temps

Résumé du poste

Mecka AI is hiring a Research Scientist to architect and train proprietary 3D reconstruction pipelines from scratch. You will transform continuous streams of real-world multi-modal data into photorealistic digital environments using 3D Gaussian Splatting and NeRFs.

You’ll integrate these assets to enhance perception pipelines and optimize for client delivery. We seek someone with deep 3D vision, experience training large-scale models in PyTorch, and CUDA kernel development to accelerate 3D

Qualifications

• Deep expertise in 3D Computer Vision, Neural Rendering, and spatial modeling.
• 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.

Responsabilités

• Design, train, and scale state-of-the-art models for dense 3D geometry extraction across multi-GPU clusters.
• Reconstruct high-fidelity digital twins of real-world environments for improved sim-to-real pipelines.
• Compress, optimize, and package massive 3D scene representations for high-framerate client viewing.
• Prototype new architectures to isolate dynamic actors from static environments and fuse sensor data.

Connaissances

3D Computer Vision

Neural Rendering

Multi-view Geometry

Spatial Modeling

PyTorch

CUDA Kernels

Large-scale 3D Training

WebGL

GPU Acceleration

Outils

CUDA

WebGL

Description du poste

About Mecka AI

Mecka AI is building the data infrastructure layer for robotics and embodied AI.
We design and operate global systems for data capture, data labeling, and hardware-enabled workflows used by leading AI labs and robotics companies to train and validate humanoid and embodied AI systems.
We work closely with frontier robotics teams to bridge real-world data, simulation, learning-based systems, and deployed hardware.

The Role

We are hiring a Research Scientist to architect and train proprietary 3D reconstruction pipelines from scratch.

You will transform our continuous stream of high-quality, real-world multi-modal data into highly accurate, photorealistic digital environments using techniques such as 3D Gaussian Splatting and NeRFs. Beyond building the core architectures, you will integrate these reconstructed environments to improve other segments of our perception pipeline and optimize these spatial assets for seamless client delivery and interactive viewing.

What You'll Work On

• Advanced Neural Reconstruction: Design, train, and scale state-of-the-art models for dense 3D geometry extraction (e.g., Gaussian Splatting, NeRFs) across multi-GPU clusters to handle massive spatial datasets.

• Sim-to-Real Integration: Reconstruct high-fidelity, physically accurate digital twins of real-world environments to provide rich spatial priors that directly improve and regularize downstream robotics pipelines, world models and other sim-to-real training.

• Client Delivery & Viewer Optimization: Compress, optimize, and package massive 3D scene representations for high-framerate rendering in client-facing viewers, ensuring clients can interact with our data without sacrificing visual fidelity.

• Emergent Perception R&D: Rapidly prototype new architectures to isolate dynamic actors from static environments, resolve algorithmic bottlenecks, and fuse novel hardware sensor integrations.

What You Bring

• 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:

• First-author publications in top-tier venues (CVPR, ICCV, ECCV) focusing on 3D deep learning, neural rendering, or spatial transformers.

• Specific projects that include deploying 3D assets to WebGL, custom rendering engines, or optimizing splats for interactive viewing that are available publicly.

Why This Role?

• The Data Advantage: Access proprietary spatial and temporal ground-truth data at a scale that most academic researchers only dream of.

• High Impact: Your spatial models and environmental reconstructions will directly define how the next generation of embodied AI agents bridge the gap between simulation and the physical world.

We are committed to creating an inclusive and supportive candidate experience. Should you require any accommodation whatsoever during the interview process, please inform us without any hesitation. Mecka is dedicated to ensuring equal treatment and opportunity in all phases of recruitment, selection, and employment, in compliance with employment law. We do not discriminate based on gender, race, religion, national origin, ethnicity, disability, gender identity/expression, sexual orientation, veteran or military status, or any other protected category. Mecka is proud to be an equal opportunity employer, fostering a culture of inclusivity and maintaining a work environment that is free from discrimination, harassment, and retaliation.

Use of Artificial Intelligence in Recruitment

Mecka uses artificial intelligence (AI) responsibly to support administrative and efficiency-focused aspects of our recruitment process. This includes activities such as drafting job descriptions, generating interview questions, note-taking and recordings, and supporting sourcing and scheduling workflows. All candidate evaluations, interviews, and hiring decisions are made by members of the Mecka team. While AI tools may assist with screening and assessment, they do not replace human judgment in selection decisions. Our use of AI is intended to streamline routine tasks, improve consistency, and enhance the overall candidate experience. We are committed to upholding principles of fairness, transparency, and accountability in all hiring activities. Mecka regularly reviews its recruitment practices to mitigate bias and to ensure alignment with applicable laws and evolving best practices.