Business Intelligence Developer Jobs in Mountain View, CA

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.

As a Senior Software Engineer in Creative Composition Intelligence, you will be driving the design, development, and productionization of advanced Machine Learning models for optimizing Ad creative composition and delivery. You will lead efforts to accelerate innovation in how we automatically construct and select the best creative elements for any given context.

In this role, you will take on new, ambiguous problems at the intersection of GenAI, ML, large-scale distributed systems, and Ad product needs. You will be expected to set technical direction, influence across teams, and mentor other engineers, as well as in creating and delivering impactful systems.

Responsibilities

• Lead end-to-end development of novel machine learning models, incorporating techniques like deep learning, reinforcement learning, and generative AI, from concept to production.
• Define the technical strategy and roadmap for key ML components, ensuring alignment with product goals and driving measurable impact through experimentation.
• Build and integrate scalable ML pipelines and services, collaborating with infrastructure and serving teams to power creative optimization.
• Analyze performance metrics, deriving insights, and implementing algorithmic improvements for creative selection, freshness, and exploration.
• Mentor engineers and promote best practices in applied machine learning and system design.