The Machine Learning Engineer role is responsible for building AI systems that can perform previously impossible tasks or achieve unprecedented levels of performance. This requires good engineering (for example: designing, implementing, and improving a massive-scale distributed machine learning system), writing bug-free machine learning code (surprisingly difficult!), and building the science behind the algorithms employed. In all the projects this role pursues, the ultimate goal is to push the field forward.
The most outstanding deep learning results are increasingly attained at massive scale, and these results require engineers who are comfortable working in a large distributed systems. We expect engineering to play a key role in most major advances in AI of the future.
We expect you to have:
2+ years of ML work experience
strong programming skills
strong interest in AI safety
excitement to scale up experiments
We’re building safe Artificial General Intelligence (AGI), and ensuring it leads to a good outcome for humans. We believe that unreasonably great results are best delivered by a highly creative group working in concert.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Health, dental, and vision insurance for you and your family
Unlimited time off (we encourage 4+ weeks per year)
Flexible work hours
Lunch and dinner each day
OpenAI is a non-profit AI research company, discovering and enacting the path to safe
artificial general intelligence.
OpenAI's mission is to build safe AGI, and ensure AGI's benefits are as widely and evenly distributed as possible. We expect AI technologies to be hugely impactful in the short term, but their impact will be outstripped by that of the first AGIs.
We're a non-profit research company. Our full-time staff of 60 researchers and engineers is dedicated to working towards our mission regardless of the opportunities for selfish gain which arise along the way.
We focus on long-term research, working on problems that require us to make fundamental advances in AI capabilities. By being at the forefront of the field, we can influence the conditions under which AGI is created. As Alan Kay said, "The best way to predict the future is to invent it."
We publish at top machine learning conferences, open-source software tools for accelerating AI research, and release blog posts to communicate our research. We will not keep information private for private benefit, but in the long term, we expect to create formal processes for keeping technologies private when there are safety concerns.