The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Provide technical leadership and people management for a team of Software Engineers delivering AI-ready training datasets and data quality infrastructure.
Architect, build, and evolve large-scale distributed data processing pipelines, signal-serving platforms, and dataset observability systems with rigorous reliability and Service Level Objective (SLO) guarantees.
Partner closely with peer tech lead managers, Über Tech Leads (UTLs), and DeepMind researchers to drive the end-to-end roadmap for pre-training, post-training, and multimodal training data delivery
Design and scale web-scale algorithms and optimization frameworks including crawl targeting, document selection, deduplication, spam/low-value filtering guardrails, and objective functions operating across hundreds of billions of documents.
Establish rigorous data quality metrics and automated anomaly detection.
Minimum qualifications
Bachelor's degree or equivalent practical experience.
8 years of experience designing, building, and operating large -scale distributed systems, with a focus on scalability, fault tolerance, and reliability.
2 years of experience in a people management, supervision/team leadership role.
Experience working with algorithms and data structures, analysis, and software design.
Experience in software engineering principles, design patterns, and system architecture.
Preferred qualifications
PhD degree in Computer Science, Machine Learning, Distributed Systems, Operations Research, or a related technical field.
Experience with algorithms and mathematical or system performance improvements.
Experience building and operating high-throughput distributed systems on infrastructure or equivalent batch and streaming frameworks.
Experience as a tech lead manager leading engineering teams in domains bridging infrastructure and machine learning.
Experience with data quality, dataset curation, value-of-data analysis, or training data pipelines for Large Language Models (LLMs) and multimodal foundation models.
Bachelor's degree or equivalent practical experience.
8 years of experience designing, building, and operating large -scale distributed systems, with a focus on scalability, fault tolerance, and reliability.
2 years of experience in a people management, supervision/team leadership role.
Experience working with algorithms and data structures, analysis, and software design.
Experience in software engineering principles, design patterns, and system architecture.
