Role Summary

This role is suited for a candidate with deeper interest and capability in machine learning systems, model development, model evaluation, inference workflows, experimentation, and analytical problem-solving. The candidate will work on model-driven systems that support product matching, classification, similarity search, explainability, automated decisioning, and quality improvement.

The role requires someone who can understand ML model behavior, analyze outputs, improve inference pipelines, measure performance, and collaborate with science and engineering teams to translate model capabilities into production workflows.

Key Responsibilities

• Build, improve, and maintain ML inference pipelines and model-serving workflows.
• Work on model evaluation, error analysis, performance tracking, and experimentation.
• Analyze model outputs to identify patterns, failure modes, precision / recall trade-offs, and improvement oppor...