Software Engineer, AI/ML, Search, Discover Videos Content

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 2 years of experience with software development in
  C++, Python, Machine Learning, Data Analysis, or 1 year of experience with an advanced degree.
• 1 year of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), NLU/Natural Language Understanding, reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical fields.
  
• 2 years of experience with Information Retrieval, Recommender Systems, Large Language Model, coLaboratory, Search Quality, Large Scale Data Processing, SQL.
• 2 years of experience with data structures or algorithms. Experience in data analysis using SQL or Python.
• Experience in Recommendation Systems, Information Retrieval, Search Quality or Search Infrastructure. Experience with ML infrastructure (e.g., model evaluation, optimization, deployment, data processing, debugging).
• Experience developing accessible technologies.
  

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

Our team’s mission is to build Multimodal Video Understanding with SOTA LLM (Large Language Models) models and develop novel, high impact applications on the various Search products and surfaces.This team is responsible for the technology that powers Video Retrieval and Ranking, and intelligence features like Key Moments, Video inputs in AIO/AIM, Video Snippets, Summaries, etc, improving direct user experience and powering marquee features on Google Search surfaces.

In this role, you will use a variety of approaches including deep learning for NLU and computer vision, as well as traditional machine learning techniques. You will also build infrastructure to support video processing, understanding, retrieval and ranking. You will work closely with indexing, frontend, PM, UX, and teams across a large number of products in Search.

In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.

Responsibilities

• Write product or system development code. Identify the gap in coverage and quality between the videos we index and show in Search products today, and those matching the product goals, through data analysis, evaluation and debugging.
• Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.
  
• Leverage SOTA multimodal LLM models to understand the video content and generate useful ranking signals. Develop and improve user modeling and personalization signals and algorithms to surface more personally
• Build, optimize and maintain the infrastructure to efficiently index and serve video content in Search.
• Develop and implement algorithmic improvement to the triggering, retrieval and ranking of videos in Search.