About the job
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 an ML/Quality Engineer on the Cloud AI Agent Quality team, you will be at the forefront of advancing the state-of-the-art for large language models in Google Cloud. You will be responsible for delivering continuous improvements to Gemini's agentic capabilities, directly supporting Cloud product goals.
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.
Qualifications
Minimum
Bachelor’s degree or equivalent practical experience.
2 years of experience programming in Python or C++.
1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).
Experience with core GenAI concepts (LLM, Multi-Modal, Large Vision Models) and text, image, video, or audio generation.
Preferred
PhD degree with specialization in Machine Learning.
3 years of experience in modeling with practical or educational experience in LLMs, and GenAI-related publications.
Experience with one or more general purpose programming languages (e.g., Python).
Excellent proficiency and communication skills in verbal and written English.