Senior Software Engineer
Updated on 2/8/2024
AI systems for practical real-world applications
Imbue is a pioneering company in the AI industry, focusing on the development of reasoning AI systems that aim to enhance human-computer interaction and productivity. Their competitive edge lies in their unique approach to training foundation models optimized for reasoning, which they then utilize to prototype agents that can accomplish larger goals safely in the real world. With a culture that values empowerment, freedom, and dignity, Imbue is leading the industry in redefining the concept of the personal computer, making it a compelling place to work.
AI & Machine Learning
Data & Analytics
San Francisco, California
Growth & Insights
6 month growth↑ 10%
1 year growth↑ 121%
2 year growth↑ 210%
Remote in USA
AI & Machine Learning
- Proficient in Python
- Familiar with PyTorch and training deep neural networks
- Experience with open source code
- Passionate about engineering best practices
- Create automated services for iterating on network architectures
- Implement new tasks in Avalon and related environments
- Optimize existing agents and models for lower latency and higher throughput
- Develop improved graphing, debugging, and error handling tools
- Experience in machine learning research
- Experience in developing AI systems
Much of the work we do at Imbue is effectively pure software engineering. Our perspective is that even machine learning research ends up being about 90% software engineering, so even without any prior machine learning knowledge, there is plenty to contribute as a normal software engineer. Even most of our machine learning research tends towards the software engineering side of the spectrum, as we prefer to automate the types of work that academic researchers typically do (ex: tuning hyperparameters, experimenting with small variations in network architectures, etc).
• Create an automated service for iterating on network architectures. Most of the work is in defining and implementing the search space over network (which are, at the end of the day, just code that defines a graph of computations).
• Implement new tasks in Avalon and related environments. We are constantly extending our systems to add newer, more complex tasks on which to train more capable agents.
• Optimize existing agents and models to make them lower latency and higher throughput.
• Develop improved graphing, debugging, and error handling tools to investigate the myriad ways that neural networks and agents fail.
• 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.
Compensation and Benefits
• Work directly on creating software with human-like intelligence.
• Generous compensation, equity, and benefits.
• $20K+ yearly budget for self-improvement: coaching, courses, conferences, etc.
• Actively co-create and participate in a positive, intentional team culture.
• Spend time learning, reading papers, and deeply understanding prior work.
• 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 $170,000–$350,000 cash, $10,000–$2,000,000 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).
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.