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Research Engineer - AI Systems & Context | Full-time | Remote/On-site

About the role

Do you consider that traditional data storage/retrieval systems are obsolete for the age of AI? That siloed databases are one of the main reasons preventing AI from species-level adoption? If yes, you'll feel right at home here.

Who you are

Are you someone who feels that AI agents are still so unstable? Do you wake up everyday thinking that AI systems need a massive upheaval and sorely need context? Context is still unsolved - and you want to be the one to fix it.

What you will do

• Designs and improves LLM memory layers for faster, sharper recall. • Builds systems for clean memory storage, retrieval, and on-the-fly updates. • Experiments with context-ranking, embeddings, and vector tricks to boost accuracy. • Turns research ideas into real, stable memory pipelines that don’t meltdown at scale. • Works with us to make LLMs remember stuff like they actually mean it.

Tell us a bit about yourself

Link to your research page, portfolio, or best work so far

Your Twitter/Linkedin handle

What is an insight in AI context and memory that you are convinced about, that might not be a popular opinion?

On a scale of 1 to 5, how would you rate your communication skills?

On a scale of 1 to 5, how would you rate your communication skills?

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How did you hear about this job?

How did you hear about this job?