Staff ML Software Engineer, Search Ecosystem

Google•Mountain View, CA

5d•$207,000 - $300,000

About The Position

Google software engineers develop technologies that help billions of users connect, explore, and interact with information. The Search Ecosystem team builds a sustainable content ecosystem for Google products, creating scalable platforms that identify knowledge gaps in AI models, source high-quality content to address them, and train models to verify performance improvements. In this role, you will help build robust systems and scalable platforms that power content acquisition for AI model training in a responsible and secure manner. You will work on a business-critical product in a fast-moving organization, contributing to impactful projects that advance artificial intelligence and Google Search. The role involves developing evaluation approaches for AI systems and data, using results to improve system performance and value models, shaping technical strategy, and building infrastructure on top of LLMs. Individual pay is determined by job-related skills, experience, and relevant education or training. The US salary range is $207,000–$300,000, plus a 20% bonus target, equity, and benefits.

Requirements

Bachelor’s degree or equivalent practical experience.
8 years of experience in software development, including 5 years of experience testing and launching software products and 3 years of experience with software design and architecture.
5 years of experience building ML systems and infrastructure, such as for model training, evaluation, deployment, or serving.
Experience integrating generative AI tools or LLM interfaces into workflows.
Experience with data processing software such as Hadoop, Spark, Beam, or Hive; strategies such as ETL, ELT, or CDC; or algorithms such as MapReduce or Flume.

Nice To Haves

Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
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 full-stack development, building back-end distributed infrastructure, and programming in Java, Python, or C++.
Experience integrating generative AI tools and understanding of AI architecture.

Responsibilities

Develop and implement frameworks and methodologies for evaluating the quality and effectiveness of AI system components and data.
Analyze evaluation results to drive improvements in system performance and underlying value models.
Play a key role in building and articulating the high-level technical strategy for the area of ownership.
Leverage knowledge of LLMs to design, build, and maintain specialized infrastructure on top of LLMs.
Drive technical projects from ideation through production in an ambiguous and fast-paced environment.