About this role
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.