Lead Data Scientist

Overview

Lead a machine learning engineering effort to improve AI products and build new ML applications, including model development, training, evaluation, and deployment at scale.

What you'll do

• Study and transform data science prototypes into AI/ML applications.
• Design AI/ML applications.
• Use large language models and vision-language models for information retrieval.
• Select appropriate annotated datasets for supervised learning.
• Develop and improve ML systems: feature engineering, algorithm selection, training, and evaluation experiments.
• Integrate trained models into application flows and deploy at scale.
• Extend ML libraries and frameworks across multiple ML tasks.

What you'll need

• 9+ years hands-on experience in AI/ML and Data Science.
• Knowledge of Python and related libraries.
• Ability to write robust, testable code and design software architecture.
• Understanding of ML techniques for feature engineering, data preprocessing, and modelling.
• Strong understanding of AI technologies including Generative AI, NLP, and Computer Vision.
• Hands-on experience leveraging language models for information retrieval.
• Familiarity with AI platforms and libraries such as TensorFlow, PyTorch, and scikit-learn.

Details

• Grade level listed as 11 (internal use).