Summary
As a 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.
This role can be either fully in-person or remote.
Example projects
• Understand and implement papers to improve areas of interest, such as automatically generating and iteratively refining code, outputting reasoning traces, and verifying or debugging code.
• Devise scientifically rigorous experiments to analyze the failure modes and benefits of different techniques.
• Contribute to our data generation pipeline for creating instruction-tuning and evaluation data
• Develop infrastructure for making fine-tuning and experimentation simpler, faster, and less error-prone.
• Work with our data and product engineers to identify areas of improvement from model results
• Leverage our existing framework to perform hyperparameter sweeps, and maintain and contribute new features to the sweep code
You are
• Very comfortable writing Python.
• Familiar with PyTorch and training deep neural networks.
• Passionate about engineering best practices.
• Self-directed and independent.
• Excellent at getting things done.
Compensation and Benefits
• Work directly on creating software with human-like intelligence
• Flexible working hours
• Time and budget for learning and self improvement
• Compensation packages are highly variable based on a variety of factors. If your salary requirements fall outside of the stated range, we still encourage you to apply. The range for this role is $140,000–$350,000 cash, $10,000–$5,000,000 in equity.
How to apply
All submissions are reviewed by a person, so we encourage you to include notes on why you're interested in working with us. If you have any other work that you can showcase (open source code, side projects, etc.), certainly include it! We know that talent comes from many backgrounds, and we aim to build a team with diverse skillsets that spike strongly in different areas.
We try to reply either way within a week or two at most (usually much sooner).
Learn more about our full interview process here.
About us
Imbue builds AI systems that reason and code, enabling AI agents to accomplish larger goals and safely work in the real world. We train our own foundation models optimized for reasoning and prototype agents on top of these models. By using these agents extensively, we gain insights into improving both the capabilities of the underlying models and the interaction design for agents.
We aim 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.
Top Skills
What We Do
We build AI systems that can reason, in order to enable AI agents that can accomplish larger goals and safely work for us in the real world. To do this, we train foundation models optimized for reasoning. On top of our models, we prototype agents to accelerate our own work, seriously using them in order to shed light on how to improve the underlying model capabilities, as well as the interaction design for agents.
We aim to rekindle the dream of the *personal* computer—for computers to be truly intelligent tools that empower us, giving us freedom, dignity, and agency to do the things we love.
