GenAI Software Engineer: ML Infra & AI

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

Job summary

Google is hiring software engineers for YouTube to develop next-generation systems and AI-enabled features at massive scale. You will work on projects spanning information retrieval, distributed computing, and AI, with opportunities to switch teams as the company grows.

Responsibilities include writing code, conducting design reviews, updating documentation, debugging issues, and implementing GenAI solutions using ML infrastructure to drive performance and user experience.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 2 years of experience programming in Python and C++.
• 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• Experience with core GenAI concepts (LLM, Multi-Modal, Large Vision Models) and with generation of text, image, video, or audio.

Responsibilities

• Write product or system development code.
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (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.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
• Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements.

Skills

Python

C++

ML infrastructure

GenAI concepts

Data structures & algorithms

Accessible technologies

Education

Bachelor's degree or equivalent

Master's degree or PhD in CS

Job description

Google is hiring software engineers for YouTube to develop next-generation systems and AI-enabled features at massive scale. You will work on projects spanning information retrieval, distributed computing, and AI, with opportunities to switch teams as the company grows.

Responsibilities include writing code, conducting design reviews, updating documentation, debugging issues, and implementing GenAI solutions using ML infrastructure to drive performance and user experience.