Opening. This role is part of the Autonomous Agents team, which conducts research into methods, models, and tools that will seek to imitate—and eventually replicate—behaviours and capabilities which make humans helpful and collaborative, and able to support one another.
What you'll do
As a Research Engineer, you will design and implementation of use-case-focussed technology prototypes, design and implementation of (often human-driven) 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, and 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.
What you need
- A strong academic record, ideally at MS/MSc/MEng level or above
- Industry experience involving engineering work pertaining to neural networks, or ML methods in general — i.e. experience with the workflow of a machine learning project, from idea prototyping to analysis and debugging
- Strong knowledge of Python, and strong software engineering skills (writing clear documentation, learning new frameworks and APIs, organizing codebases)
- Strong knowledge of machine learning, working knowledge of statistics
- Experience working with accelerators like GPUs and TPUs
- Experience with large-scale data processing frameworks (e.g., Apache Beam, Spark) or distributed training infrastructure
