The role involves designing and building scalable, reliable, and secure services to support the machine learning lifecycle. Responsibilities include creating libraries that facilitate the transition of models from experimentation to production environments. The individual will collaborate with product and engineering teams to enhance development velocity and MLOps maturity. The position requires addressing complex technical challenges across various systems and processes. Additionally, the role focuses on developing infrastructure for notebooks, model training, and large language model applications.

Candidates must possess at least two years of professional software development experience with a focus on distributed systems and service oriented architecture. Proficiency in the full software development lifecycle, including design, implementation, testing, and operations, is required. Applicants should have practical experience with production machine learning platforms, MLOps, or large language model applications. The role also requires experience managing high availability and low latency systems. No specific degree is mentioned as a requirement.