You will work in one of FAR.AI's research workstreams, developing scalable implementations of machine learning algorithms and use them to run scientific experiments. You will be involved in the write-up of results and credited as an author in submissions to peer-reviewed venues (e.g. NeurIPS, ICLR, JMLR). While each of our projects is unique, your role will generally have: Flexibility. You will focus on research engineering but contribute to all aspects of the research project. We expect everyone on the project to help shape the research direction, analyze experimental results, and participate in the write-up of results. Variety. You will work on a project that uses a range of technical approaches to solve a problem. You will also have the opportunity to contribute to different research agendas and projects over time. Collaboration. You will be regularly working with our collaborators from different academic labs and research institutions. Mentorship. You will develop your research taste through regular project meetings and develop your programming style through code reviews. Autonomy. You will be highly self-directed. To succeed in the role, you will likely need to spend part of your time studying machine learning and developing your high-level views on AI safety research. About You This role would be a good fit for someone looking to gain hands-on experience with machine learning engineering and develop their research skills. Interested applicants may be transitioning from a software engineering background, or looking to grow an existing portfolio of machine learning research.