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.
BASIC QUALIFICATIONS:
– 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
– 3+ years of non-internship professional software development experience.
– Experience programming with at least one software programming language
– Master's degree or equivalent.
PREFERRED QUALIFICATIONS:
– 3+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience.
– Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence.
– 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience.
– Master's degree in computer science or equivalent.
– 3+ years of machine learning, statistical modeling, data mining, and analytics techniques experience.
