Software Engineer, Search Platforms, GenAI Content

Job description

Develop and deploy GenAI technology to empower content understanding and AI generated content framework. Be responsible for conducting applied research on new GenAI techniques to explore the new content experience and direction. Contribute to content tech areas evolvements including multimodality content understanding (tagging, semantic, reasoning, etc.), agentic AI content generation with proper evaluation, AI generated content, features, signal building and measurements, and rebasing the GenAI empowered knowledge graph/topic spaces with advanced framework, and structure. Be responsible for holistic content modeling and supporting infrastructure that yield our content understanding across different content types, which in turn drives high-fidelity and consistent downstream product experiences across Search, etc. Enable downstream content applications with those AI exploration capabilities; and move the corresponding product metrics. Minimum Qualifications: Bachelor's degree or equivalent practical experience. 8 years of experience with software development in one or more programming languages, and with data structures and algorithms. 8 years of experience testing, maintaining or launching software products, and 5 years of experience with software design and architecture. 8 years of experience with ML/AI algorithms and tools, deep learning or other AI/ML modeling. 7 years of experience leading technical project strategy, ML design, and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). 2 years of experience with GenAI techniques (e.g., LLMs, multi-modal, large vision models) or with GenAI-related concepts (language modeling, computer vision). Preferred Qualifications: PhD in Computer Science, Statistics, or related fields. Experience in GenAI related model fine tuning, large language models building or product enablement exploration. Experience in successfully applying GenAI and machine learning approaches to real-world content problems. Experience with deep learning frameworks such as JAX, TFX or TFlex. Strong mathematical skills with knowledge of statistical methods. Excellent programming skills leveraging GenAI tools.