Post-Training is responsible for training the models to be deployed into ChatGPT, the API, and future products. The team partners closely with research and product teams across the company, and conducts research as a final step to prepare for real world deployment to millions of users, ensuring that our models are safe, efficient, and reliable.
About the Role
We are looking for a self-starter full stack engineer who can help us rapidly prototype and develop internal products or tools used by researchers, such as visualization for our evaluation of models. You should be comfortable being truly full stack, such as building front-end from scratch and debugging backend and data pipelines. Ideal candidates are comfortable being scrappy and working independently at fast speeds.
This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
In this role, you will:
Rapidly prototype and build tooling or visualization for researchers.
Collaborate with research teams to build full stack tooling.
Design, implement, test, and debug code across our stack.
Very comfortable refactoring codebases
Strong background in writing maintainable, testable, clean code.
Enjoyment of code quality, refactoring, and building robust internal codebases.
Have experience building products that end users interface with, or building internal tools.
Have experience experience shipping things quickly with competing priorities or deadlines.
Proficiency with Python
Are a team player, willing to do a variety of tasks that move the team forward.