As a remote machine learning engineer, you’ll work very closely with a senior member of our research team on cutting-edge deep learning research, infrastructure, and tooling towards the goal of creating general human-like machine intelligence.
• Implement a self-supervised network using contrastive and reconstruction losses.
• Create a library on top of PyTorch to enable efficient network architecture search.
• Open source internal tools.
• Implement networks from newly published papers.
• Work on tools for simple distributed parallel training of deep neural networks.
• Develop more realistic simulations for training our agents.
• Design automated methods and tools to prevent common issues with neural network training (e.g. overfitting, vanishing gradients, dead ReLUs, etc).
• Create visualizations to help us deeply understand what our networks learn and why.
• Very comfortable writing Python.
• Familiar with PyTorch and training deep neural networks.
• Excited to work on open source code.
• Passionate about engineering best practices.
• Self-directed and independent.
• Excellent at getting things done
• Work directly on creating software with human-like intelligence
• Very generous compensation
• Flexible working hours
• Work remotely
• Time and budget for learning and self improvement