Want to build general-purpose artificial intelligence for 3D perception and model building? Common Sense Machines is developing a platform that learns to translate the visual world into a 3D simulation for people and machines. We are a seed-stage venture-backed company founded by a group of PhDs and faculty from MIT. We have worked on large AI systems at DeepMind and have collectively founded three companies with successful exits. 

We are looking for a machine learning engineer to train generative models on large scale datasets and compute infrastructure. 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. You will have a broad range of responsibilities including:

• Implementing and scaling new deep learning architectures in close collaboration with researchers.
• End-to-end optimization and deployment of our machine learning pipeline.
• Develop software libraries and accelerators for training neural networks interfacing with search and reinforcement learning algorithms on distributed systems.
• Provide, maintain and optimize high-quality Python/C++ code.

• Expert-level knowledge of PyTorch and distributed deep learning.
• Proven ability to rapidly translate a research paper into prototypes (industry or research labs experience).
• Experience designing, scaling, and optimizing machine learning infrastructure (e.g., distributed cloud computing, feature pipelines, visualization, MLOps, monitoring).
• Team-oriented and comfortable wearing multiple hats in a growing company.

We provide competitive compensation (cash and stock options), flexible work hours, unlimited vacation, and top-tier medical coverage. Our headquarters is in Cambridge, MA. Common Sense Machines is an equal opportunity employer and we are committed to creating a diverse and inclusive environment for all employees.