US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Design and roll out the next-generation multimodal and encoder architecture across workhorse models, integrating frame-level video embeddings in partnership with Google DeepMind.
Lead the evolution of Content Safety’s teacher stack by migrating to next-generation Gemini models and establishing In-Context Learning Video.
Lead the design of Policy enforcement RAG (PeRAG), a low-latency, high-precision retrieval system backed by a unified Long-Term Memory service.
Lead the design of a greenfield Model Debug and Gap Mitigation Agent to automatically diagnose teacher-student distillation gaps.
Provide technical leadership on high-impact projects.
Minimum qualifications
Bachelor’s degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience leading ML design and optimizing end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).
2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
Experience designing and operating distributed computing systems for large-scale AI/ML workloads.
Experience with Large Language Models (LLMs), Natural Language Processing, or Generative AI.
Preferred qualifications
Master's degree or PhD in Computer Science, a related field, or equivalent practical experience.
8 years of experience with data structures and algorithms.
3 years of experience in a technical leadership role leading project teams and setting technical direction.
3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
Experience as a full-lifecycle ML engineer in training dataset curation, modern neural architectures, evaluation frameworks, and post-deployment iterations.
Ability to work with cross-functional teams.
Bachelor’s degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience leading ML design and optimizing end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).
2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
Experience designing and operating distributed computing systems for large-scale AI/ML workloads.
Experience with Large Language Models (LLMs), Natural Language Processing, or Generative AI.
