Senior Software Engineer, ML Evaluation & Introspection Infrastructure

About this kind of role

What a Senior Software Engineer, ML Evaluation & Introspection Infrastructure usually does. The employer's own details are in the listing.

Typically does: Designs, develops, and maintains infrastructure and tools to evaluate machine learning models and understand their behavior. This includes building systems for automated testing, performance monitoring, and debugging of ML pipelines. They also work on tools that enable data scientists and ML engineers to introspect model decisions and identify areas for improvement. A key focus is ensuring the reliability, scalability, and efficiency of ML evaluation processes.

Tools and skills: Proficiency in Python, experience with cloud platforms (like AWS, Azure, or Google Cloud), familiarity with machine learning frameworks (TensorFlow, PyTorch), and strong skills in software engineering principles, data structures, and algorithms are generally required.

Good fit for: Individuals with a strong background in software development and a passion for machine learning, who enjoy building robust and scalable systems to support complex analytical workflows, are a good fit.