Summary
Initio is building AI systems for autonomous scientific discovery.
We believe one of the most important capabilities for AI is the ability to dramatically accelerate science and technology development by building systems that can reason about hard technical problems, run useful computational experiments, learn from the results, and improve autonomously.
We are hiring for Member of Technical Staff roles to help build that capability. This is an early technical role with broad scope, high ownership, and direct influence over the direction of the system.
We are looking for exceptional technical talent across software engineering, AI research, AI engineering, scientific computing, computational science, and related areas — including people whose work does not fit cleanly into any one category. What matters is not the domain you come from, but whether you can help make the system more capable.
What you’ll work on
You will work on the systems, experiments, and technical foundations that make autonomous scientific discovery possible. Depending on your strengths, this may include:
- Building AI systems that can plan, execute, and learn from computational experiments
- Running discovery experiments with the system and converting the results into system improvements
- Designing evaluations and experimental setups tied to meaningful scientific or technical goals
- Building infrastructure for reliable, reproducible, high-throughput computational research
- Building harnesses that turn models into systems capable of carrying out computational research loops
- Enabling the system to implement, test, and extend ideas from technical papers
- Developing new methods for AI-assisted and AI-driven research
- Bringing deep domain expertise from science, engineering, mathematics, or other technical fields into the design and evaluation of the system
You may be a fit if
- You have exceptional technical ability in at least one area relevant to autonomous discovery
- You have strong research taste and are good at running experiments that produce useful signals
- You know what rigor means in your domain and hold your work to that standard
- You have deep expertise in a computational or scientific domain, including domains outside the usual AI-for-science categories, and are excited about getting AI systems to make real progress there
- You are comfortable working on open-ended technical problems
- You are motivated by the possibility of building AI systems that substantially speed up scientific and technological progress
What we value
We value people who can move quickly without becoming sloppy, hold themselves to a high standard of evidence, and stay oriented toward making the system more capable.
We care about demonstrated ability: systems you have built, research you have done, problems you have solved, or discoveries you have helped make.
This work sits at the intersection of AI, software, and science. Progress requires judgement, rigor, and the ability to select meaningful problems that generate useful signals for both scientific understanding and system improvement.
If you want to work on one of the most important technical problems in AI, we would like to hear from you.
How to apply
Send us your resume and anything else that helps us understand how you think and what you can do. This might include code, GitHub, papers, technical writing, projects, demos, experiments, or examples of systems you have built.
We are especially interested in work that shows exceptional technical ability, strong judgement, and the ability to turn hard problems into progress.