Software Engineer, Real-Time Ads Personalization & Semantics

Google; Mountain View (CA); On-site; USD 147,000 - 210,000; Full time

Job summary

Google is seeking software engineers to advance end-to-end personalization and content recommendation at scale. You will work on building real-time infrastructure and representations of user content, applying state-of-the-art AI to ads and recommendations across large-scale data.

The role emphasizes cross-team collaboration, system design, and deployment of machine learning models in production, with opportunities to expand into research areas and novel AI techniques.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience programming in Python or C++.
• 1 year of experience building and deploying recommendation systems models in production.
• 1 year of experience with ML infrastructure (e.g., model deployment, evaluation, data processing).
• Experience with Large Language Models (LLMs), Multi-Modal, or Large Vision Modeling.

Responsibilities

• Write and test product or system development code.
• Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
• Review code developed by other developers and provide feedback to ensure best practices.
• Build model and architectural components that provide effective attention for ads over user preferences and history.
• Design real-time infrastructure and representations of user viewed content.

Skills

Python

C++

Recommendation systems

ML infrastructure

LLMs / Multimodal / Vision

Education

Bachelor’s degree

Job description

Google is seeking software engineers to advance end-to-end personalization and content recommendation at scale. You will work on building real-time infrastructure and representations of user content, applying state-of-the-art AI to ads and recommendations across large-scale data.

The role emphasizes cross-team collaboration, system design, and deployment of machine learning models in production, with opportunities to expand into research areas and novel AI techniques.