Research Engineer II, Agents AI

A Research Engineer supports Applied Scientists in the team by helping to build tools, experiment frameworks, and infrastructures. A Research Engineer may be called to directly facilitate science benchmarking, and deep dive on any deep learning related technical problems. He/she may be called to lead or facilitate a joint project between science and engineering team.

Key job responsibilities:
* Participate research and development: direct or indirectly contribute to developing latest Retrieval Augmented Generation technologies, fine-tuning techniques for embedding models and LLMs.
* Tool development: build and improve toolings that applied scientists would need, including scalable science experiment frameworks, low-latency testing pipelines, data collection/annotation/evaluation web applications.
* Expedite science to production: bridge the gap between science and engineering teams, help to investigate and mitigate gaps between science and engineering pipeline. Help to merge both pipelines to one, or making components within the two interchangeable. Work towards a fast science-to-production paradigm.
* Science code quality control: serve as gate keeper, review and hold science code quality to production standard.
* Manage science infrastructure: act as admin to manage all science AWS account, including patch any security risks, build templates, AWS Cops, conduct cost reduction operations.