Description

Conduct research to solve large-scale industry problems at the AI frontier, focusing on ML Explainability, Safety, and Auditing.

This role is on-site.

Responsibilities

• Research advanced problems involving ML Explainability, Safety, and Auditing.
• Develop new techniques for ML Observability.
• Collaborate with MLEs and SDEs to roll out and stabilize new features.
• Select datasets and problem types to address core research challenges.
• Create and maintain technical and product documentation.

Required Skills

• 3+ years of experience in Machine Learning or Deep Learning.
• Hands-on experience with PyTorch or TensorFlow.
• Practical knowledge of ML Explainability methods including SHAP, LIME, IG, and CEM.
• Experience implementing semi-supervised learning techniques and GANs.
• Proficiency working with textual, tabular, categorical, and image datasets.
• Strong fundamentals in MLOps and productionizing ML models.
• Ability to deploy code in cloud or on-premise environments.
• Strong academic background in machine learning and deep learning concepts.

Key Skills

Education

Not specified