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Snapshot
We are looking for Research Engineers to join the Autonomous Assistants team, and produce/support research in the development of next-generation technologies to power increasingly autonomous agents which strive to assist, support, and supplement humans in their daily personal and professional lives.
About Us
Artificial Intelligence could be one of humanity’s most useful inventions. We’re a team of scientists, engineers, machine learning authorities and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.
The role
The Autonomous Assistants team will conduct research into methods, models, and tools which will seek to imitate—and eventually replicate—behaviours and capabilities which make humans helpful and collaborative, and able to support one another. The team will have a strong focus on application and evaluation-driven research, whereby fundamental questions about autonomy, responsibility, and intelligent reasoning and understanding, are pragmatically studied under the lens of whether and how they improve the ability of our systems to practically help us in real-world tasks.
Research engineers in this team are expected to help with some/all of the following key responsibilities:
- Design and implementation of use-case-focussed technology prototypes
- Design and implementation of evaluation protocols
- Partner with research scientists to design and/or implement candidate technical solutions to practical challenges surrounding the assistant technology use-case(s) being focussed on by the team
- Keep up with technical developments with regard to tooling, frameworks, and other technologies surrounding: the training and fine-tuning of large models; the collection, processing, and storage of data; the design , implementation, and running of shared evaluation exercises; LLMs (including multi-modality); tool-use; reasoning, memory, and self-improvement; etc.
About you
In order to set you up for success as a Research Engineer, we look for the following skills and experience:
- A strong academic record, ideally at MS/MSc/MEng level or above
- Ideally, shown experience involving engineering work pertaining to neural networks, or ML methods in general — i.e. a background in the workflow of a machine learning project, from idea prototyping to analysis and debugging
- Solid understanding of Python/C++, and strong software engineering skills (writing clear documentation, learning new frameworks and APIs, organizing codebases)
- Proven knowledge of machine learning, and understanding of statistics
- Experience working with accelerators like GPUs and TPUs
In addition, the following would be an advantage:
- Experience with data collection/annotation and evaluation/benchmarking, including benchmark design
- Experience with LLMs, in particular with fine-tuning and associated methods (RLHF, preference optimization, etc)
- Experience with the production and dissemination of research artefacts (papers, technical reports, research framework documentation)
- Experience with UX/UI, or at least the ability to partner with specialist engineers to deliver useable software prototypes
- A drive for developing working prototypes of ML-powered technology, especially in the assistant technology space
Applications close at 6pm BST on 26th September and will be reviewed on a rolling basis.