Remote and San Francisco, CA /
At Generally Intelligent, we leverage large amounts of compute to make our small research team more effective. This role is about enabling and supporting those large-scale compute efforts and all of the other software infrastructure that goes into making research a pleasant, seamless experience for the rest of the team, especially as we scale to increasingly higher scale systems.
One benefit of this role is that, since we have no product or customers, you will not be on-call. All of our engineers are (and will continue to be) sufficiently empowered to fix their own infrastructure issues.
• Prototype and develop infrastructure for increasingly large-scale models
• Create tools and scripts for common research workflows (ex: changing the priority of a currently running job)
• Integrating with new cloud providers and enabling us to run experiments seamlessly across different clouds and physical infrastructure
• Consolidate our logging efforts
• Improve security policies and procedures
• Automate provisioning of new physical servers, NFS, etc
• A good software engineer. We are strong adherents of "infrastructure as code", so you will be writing (and reading) lots of Python, bash, etc.
• Passionate about enabling other engineers and creating good tooling for developers to interact with infrastructure in an automated way.
• Experienced enough with dev ops to be properly opinionated. You should understand the trade-offs of various approaches and technologies, and not be dogmatically tied to a single tool.
• Careful and detail oriented. We do science and care deeply about the correctness of the results. Our infrastructure reflects this--we highly value robustness and ensuring that systems run reliably and correctly.
• 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.
• Frequent team events, dinners, off-sites, and hanging out.
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).
We started Generally Intelligent because we believe that software with human-level intelligence will have a transformative impact on the world. We’re dedicated to ensuring that that impact is a positive one.
We have enough funding to freely pursue our research goals over the next decade, and our backers include Y Combinator, researchers from OpenAI, Astera Institute, and a number of private individuals who care about effective altruism and scientific research.
Our research is focused primarily on self-supervised and generative video and audio models. We’re excited about opportunities to use simulated data, network architecture search, and good theoretical understanding of deep learning to make progress on these problems. We take a focused, engineering-driven approach to research.