Shikib Mehri

Shikib Mehri

Director of Research at Contextual AI, managing a team of 5 researchers working on LLMs and agents. Previously an Applied Scientist at Amazon, where I helped found the Alexa LLM post-training team (which became Amazon AGI). PhD from CMU LTI [thesis] (2022) and BSc from UBC (2018). Always looking to meet exceptional researchers and interns — check out our open roles.

Recent: (1) GLMv2 reached #1 on the FACTS leaderboard. (2) LMUnit was open-sourced and achieved #1 on RewardBench2. (3) AgentLens launched as a multi-agent evaluation system. (4) GLM covered in VentureBeat. (5) Contextual AI's post-training recipe featured as a Google Cloud case study.

I most enjoy product-driven research — work that enables next-generation user experiences through strong problem formulation. Currently focused on multi-agent systems, continuous learning, memory, agentic evaluation, and context representations. Key areas include:

BSc from UBC (2018) with internships at Meta (shipped first subword neural MT), Microsoft, and Amazon, and 2 years in bioinformatics at BC Children's Hospital (graph-based genome representation). PhD at CMU LTI (2018–2022) on dialog systems [thesis], advised by Dr. Maxine Eskenazi; was also a TA and research mentor throughout both degrees. After my PhD I was an Applied Scientist at Amazon, where I helped found the Alexa LLM post-training team (led early SFT, data collection, and owned RM/eval) which became Amazon AGI. I then joined Contextual AI as a Member of Technical Staff (Jan 2024), was promoted to Technical Lead Manager (May 2024), and then Director of Research (Aug 2025).