Machine Learning Evaluation Engineer
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Key details
What makes this role novel
ML evaluation engineering—the systematic design of metrics, failure analysis frameworks, and evaluation infrastructure specifically for large-scale ML systems—is a distinct discipline that emerged in the last 3–4 years as companies scaled foundation models and needed specialized roles to measure and debug them beyond traditional validation.
Job Description
We are looking for a highly motivated Machine Learning Evaluation Engineer to join our team and help define and drive the evaluation of advanced machine learning and computer vision technologies. You will work closely with algorithm, data, and engineering teams to build scalable evaluation methodologies, uncover model weaknesses, and turn complex data into actionable insights.
You will play a key role in ensuring that our ML systems deliver high-quality, robust experiences across diverse real-world scenarios. The ideal candidate combines strong fundamentals in classical machine learning and computer vision with hands-on experience in metrics design, data analysis, failure analysis, visualization, and evaluation infrastructure. You should also be comfortable leveraging modern AI-assisted tools and workflows to improve engineering efficiency and accelerate analysis.
Audit details(provenance, verification trail, raw fields)
Core fields
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