Senior ML Systems Engineer — Personalization

Google; Mountain View (CA); On-site; USD 174,000 - 252,000; Full time

Job summary

Google is seeking software engineers in Mountain View, CA to advance end-to-end personalization and real-time understanding of user interactions. You will contribute to building real-time infrastructure and representations of user viewed content, enabling powerful personalization and content recommendation in Ads.

Role focuses on end-to-end enrichment of personalization pipelines with ML and AI technologies, collaborating with research and infrastructure teams to scale impact and accuracy across

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience programming in Python or C++.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 2 years of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).
• 2 years of experience with Large Language Model (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 (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
• Build real-time infrastructure and representations of user viewed content.

Skills

Python or C++

Testing & architecture

ML infrastructure

LLMs / Multi-Modal / Vision

Education

Bachelor’s degree or equivalent practical experience

Master’s degree or PhD in CS or related field

Job description

Google is seeking software engineers in Mountain View, CA to advance end-to-end personalization and real-time understanding of user interactions. You will contribute to building real-time infrastructure and representations of user viewed content, enabling powerful personalization and content recommendation in Ads.

Role focuses on end-to-end enrichment of personalization pipelines with ML and AI technologies, collaborating with research and infrastructure teams to scale impact and accuracy across