US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Research emerging technology and make trade-off decisions between immediate wins and long-term stability.
Modify training and serving infrastructure to support new modeling techniques and products.
Collaborate closely with team members and partners to build systems that integrate seamlessly across the ecosystem.
Improve robustness, reliability, and usability of machine learning infrastructure.
Engage with modeling teams to explore pain points and identify novel use cases.
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 state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
Experience building and architecting ML systems and infrastructure (e.g., for model training, evaluation, deployment, serving).
Experience designing and operating distributed computing systems for large-scale AI/ML workloads.
Preferred qualifications
Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
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 in Machine Learning modeling, specifically with Large Language Models (LLMs).
Experience in distributed Machine Learning system design.
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 state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
Experience building and architecting ML systems and infrastructure (e.g., for model training, evaluation, deployment, serving).
Experience designing and operating distributed computing systems for large-scale AI/ML workloads.
