Want to build general-purpose artificial intelligence for 3D perception and model building? We are looking for a machine learning engineer to develop, train, and, and scale machine learning systems at the intersection of deep learning, computer graphics, and 3D vision. You will be part of a small but growing team of engineers and scientists building 3D generative models to capture an unprecedented level of detail and diversity of physical objects. Responsibilities include:
- Implement, scale, optimize and deploy unsupervised methods for 3D reconstruction with a focus on neural differentiable rendering systems and implicit neural representations (e.g., NeRF, volumetric rendering).
- Build software libraries and accelerators for neural differential rendering and for training large-scale neural networks interfacing with search and reinforcement learning algorithms on distributed systems.
- Train large scale distributed deep learning models (Transformers, CNNs, etc) on massive internal datasets.
- Create and optimize high-quality Python/C++ code.
- Knowledge of implicit neural representations, differential rendering, PyTorch, and distributed deep learning.
- Proven ability to rapidly translate a research paper into prototypes (industry or research labs experience). Work in close collaboration with researchers and engineers.
- Experience designing, scaling, and optimizing machine learning infrastructure (e.g., distributed cloud computing, big data pipelines, visualization, MLOps, monitoring).
- Team-oriented and comfortable wearing multiple hats in a growing company.
- Drive to create an artificial intelligence breakthrough by building machines with human-level common sense and scale the latest machine learning technology.
- Competitive salary
- Early-stage startup equity
- Medical, dental, and vision insurance
- 401K with employer match
- Hybrid office / WFH with flexible work hours
- Publication opportunities
- Science and engineering-driven culture