Research Engineer / Scientist, Self-Improvement

Job description

SOLVING SELF-IMPROVING SUPERINTELLIGENCE The human brain is a sponge. Today’s AI brains are brittle and rigid. At Letta, we’re building self-improving artificial intelligence: creating agents that continually learn from experience and adapt over time. Founded by the creators of MemGPT from UC Berkeley’s Sky Computing Lab (the birthplace of Spark and Ray). Backed by Jeff Dean, Clem Delangue, and pioneers across AI infrastructure. Our agents already power production systems at companies like 11x https://www.letta.com/case-studies/11x and Bilt Rewards https://www.letta.com/case-studies/bilt, learning and improving every day. We’re assembling a world-class team of researchers and engineers to solve AI’s hardest problem: making machines that can reason, remember, and learn the way humans do. Note that this role is in-person (no hybrid), 5 days a week in downtown San Francisco. YOUR ROLE You will develop methods for agents that self-improve after training. At Letta, you'll work with a world-class, tight-knit team of AI researchers and engineers towards our vision of self-improving superintelligence. Advance the field through open publishing of research through papers, technical reports, blog posts, and open-source code. WHAT YOU’RE RESPONSIBLE FOR: - Developing prompt optimization and system prompt learning methods that allow agents to continuously learn from long-horizon tasks - Developing methods allow agents automatically generate and test out hypotheses in an environment, or seek out and improve their own weaknesses - Improving the efficiency of learning from long-running agentic tasks - Designing and running experiments to measure self-improvement scalably WHAT WE'RE LOOKING FOR: - Expertise in machine learning, in particular LLMs and continual learning - Familiarity with agent frameworks and prompt optimization - Track record of impactful research (breakthrough publications and/or open-source contributions) - Ability to balance execution speed with empirical rigor - Real-world impact beyond pure academic work OUR CULTURE SIGNS IT COULD BE A GREAT FIT: - You want to maximize your impact: you want work on a small, incredibly talented team where every individual plays a huge role in the team's success. You wonder what it would have been like to be at OpenAI when it was just a dozen people, or Google when it was just a couple of grad students in a garage. - You’re excited to go head-to-head with tech giants, frontier labs, and other startups that are many times our size in both headcount and funding. - You are fundamentally opposed to closed frontier AI that is controlled by a handful of billionaires and private tech companies. SIGNS IT’S A BAD FIT: - You like stability, and get stressed out when there’s nobody telling you exactly what to do. We look for people that thrive in ambiguity and can intuit the most important problems by talking to customers and dogfooding our product. - You want to work a 9-5, and value clear separation of work from life. The stakes are the highest they've ever been, and the only moat is execution velocity. Operating on a strict 9-5 guarantees failure. - You value titles or want to people-manage. Letta is a flat company where every researcher and engineer is an individual contributor. OUR INTERVIEW PROCESS: - Initial screen (30 min) - Technical screen (1-1.5 hours) - Paid in-person work trial (2 days onsite in SF)