G

Google

Runs Search and YouTube and builds Gemini AI

Staff Software Engineer - AI Foundry Data Quality and Training Data

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeSan Jose, CA, USAIn-person

About the Job

Requirements

  • A bachelor's degree or equivalent practical experience is required.
  • At least 8 years of experience designing, building, and operating large-scale distributed systems, with a focus on scalability, fault tolerance, and reliability, is required.
  • At least 2 years of experience in a people management, supervision, or team leadership role is required.
  • Experience working with algorithms and data structures, analysis, and software design is required.
  • Experience in software engineering principles, design patterns, and system architecture is required.

Responsibilities

  • 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 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 and low-value filtering guardrails, and objective functions operating across hundreds of billions of documents.
  • Establish rigorous data quality metrics and automated anomaly detection.
  • Guide the Data Quality team and define the end-to-end strategy and execution for data quality, targeting intelligence, and evaluation for strategic datasets powering DeepMind and Search.
  • Lead efforts to build and scale algorithmic selection pipelines, feedback loops, and dataset reliability frameworks across large-scale datasets, including web pages, code repositories, scientific documents, and multimodal assets, to advance pre-training, post-training, and multimodal capabilities of Gemini and future foundation models.

Desired Qualifications

  • A PhD degree in Computer Science, Machine Learning, Distributed Systems, Operations Research, or a related technical field is preferred.
  • Experience with algorithms and mathematical or system performance improvements is preferred.
  • Experience building and operating high-throughput distributed systems on infrastructure or equivalent batch and streaming frameworks is preferred.
  • Experience as a tech lead manager leading engineering teams in domains bridging infrastructure and machine learning is preferred.
  • Experience with data quality, dataset curation, value-of-data analysis, or training data pipelines for Large Language Models (LLMs) and multimodal foundation models is preferred.

About the Company

Google

Runs Search and YouTube and builds Gemini AI

Google runs the world's most used search engine and free services such as YouTube, Android, and Gmail, and it builds the Gemini AI models that work inside them. In 2017, its researchers invented the transformer, the neural network design behind ChatGPT and most other AI chatbots. People use these services without paying, and Google earns most of its money from ads placed beside search results and YouTube videos. Businesses rent computing power and Gemini models through Google Cloud, and Google also sells subscriptions and Pixel phones. Larry Page and Sergey Brin founded Google in 1998 as Stanford PhD students; it is based in Mountain View, California, United States, and is the main business of parent company Alphabet.

Company size
10,001+
Company stage
IPO
Headquarters
Mountain View, CA
Founded
1998

Recently Posted Jobs

Explore more opportunities at Google

See more jobs