Research Engineer

About the Role

We organize our team as Members of Technical Staff, with significant overlap between scientist and engineer roles. As an engineer, you will develop scalable implementations of machine learning algorithms and use them to run scientific experiments. You can contribute to open source codebases such as Pytorch, Hugging Face Transformers and Accelerate. You will receive engineering mentorship via code review, pair programming and regular 1-to-1s.

Alongside the scientists, you will be involved in the write-up of results and credited as an author in papers.

You are encouraged to develop your research taste, proposing novel directions and joining a research pod which suits your interests. You are welcome to take time to study and to attend conferences free of charge. Our technical team is organized into research pods to enable continuity of organizational structure whilst each pod can pivot through varied research projects.

Beyond FAR.AI, you can work with national AI safety institutes, frontier model developers and top academics.

It is essential that you:

• Have significant software engineering experience or experience applying machine learning methods
  . Evidence of this may include prior work experience, open-source contributions, or academic publications.
• Have experience with at least one object-oriented programming language (preferably Python
  ).
• Are results-oriented and motivated by impactful research.

It is preferable that you have experience with some of the following:

• Common ML frameworks like Py Torch or Tensor Flow
  .
• Natural language processing or reinforcement learning
  .
• Operating system internals and distributed systems
  .
• Publications or open-source software contributions.
• Basic linear algebra
  , calculus
  , probability
  , and statistics
  .

We encourage applications from strong software engineers who are new to ML, and from academics without industrial experience in software engineering.