AI Engineer

Overview

• Model Development & Optimization: Research, design, implement, and optimize machine learning/deep learning models (e.g., NLP, Computer Vision, Recommendation Systems, Time-Series Forecasting).
• Engineering & Deployment: Productize algorithms and models by building highly available, scalable AI services. Manage model deployment, monitoring, and continuous iteration (MLOps).
• Data Processing: Build and maintain efficient data processing pipelines for data cleaning and feature engineering, ensuring high data quality.
• Technical Innovation: Stay abreast of the latest advancements in AI from both academia and industry. Conduct proof-of-concept evaluations and apply cutting-edge technologies to real-world projects, enhancing product intelligence and user experience.
• Cross-Functional Collaboration: Work closely with cross-functional teams, including Product Managers, Software Engineers, and Data Engineers, to ensure the successful ...