Design, build, and maintain MLOps pipelines for training, testing, deploying, and monitoring AI/ML models in production, ensuring stable, reliable, and scalable performance.
4+ years as a software engineer, data engineer, or AI/ML practitioner writing technical design documents, data pipeline documentation, or API specifications
Participate in building large-scale (10 million to 100 million) e-commerce recommendation algorithms and systems, including commodity recommendations, live stream recommendations, short video recommendations etc in TikTok.
Develop foundational techniques for compressing large AI models, specifically targeting LLMs, MLLMs, and Diffusion Models, to significantly reduce their parameter count and memory footprint without compromising performance.
Design, architect, and build end-to-end AI products, including data ingestion pipelines, feature engineering, model training and inference, APIs, web applications, and observability frameworks.
Data analysis and insights: Perform exploratory data analysis, generate insights, and present findings to stakeholders. Use statistical methods and visualization techniques to communicate complex concepts and patterns effectively.
Contribute to unified AI/ML capabilities by integrating classical ML models with Generative AI platforms (primarily AWS Bedrock) for applications in semiconductor manufacturing and risk analytics.
Build agentic solutions (software development): Design and build full-stack systems and AI agents, writing production-grade code that takes solutions from first prototype through to stable production.
4+ years as a software engineer, data engineer, or AI/ML practitioner writing technical design documents, data pipeline documentation, or API specifications
The Technical Track (Senior AI Engineer / Tech Lead): Command deeper architectural ownership, pioneer core AI strategies, and drive high-stakes technical decisions, or the