- 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.
You are: - 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.
Benefits: - 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
About the company:Imbue builds AI systems that reason and code, enabling AI agents to accomplish larger goals and safely work in the real world. Imbue trains its own foundation models optimized for reasoning and prototype agents on top of these models. By using these agents extensively, they can gain insights into improving both the capabilities of the underlying models and the interaction design for agents.
Imbue aims to rekindle the dream of the *personal* computer, where computers become truly intelligent tools that empower us, giving us freedom, dignity, and agency to pursue the things we love.
WorksHub are not directly affiliated/are not a direct part of Imbue
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Remote Machine Learning Engineer - San Francisco, United States - Imbue
Description
Summary:
As a remote machine learning engineer, you'll work very closely with a senior member of Imbue's research team on cutting-edge deep learning research, infrastructure, and tooling to create general human-like machine intelligence.
Example projects: