About the role
What will you do at Google?
MINIMUM QUALIFICATIONS:
* Bachelor's degree in Computer Science, a related technical field, or
equivalent practical experience.
* 8 years of experience in software development.
* 7 years of experience leading technical project strategy, ML design, and
working with industry-scale ML infrastructure (e.g., model deployment, model
evaluation, data processing, debugging, fine tuning).
* Experience building quality evaluation frameworks for large language models.
* Experience building and deploying recommendation systems models (retrieval,
prediction, ranking, personalization, search quality, embedding) in
production.
PREFERRED QUALIFICATIONS:
* Master’s degree or PhD in Engineering, Computer Science, or a related
technical field.
* 5 years of experience in a technical leadership role leading project teams
and setting technical direction.
* Experience building advanced offline and online quality evaluation frameworks
for Large Language Models (LLMs).
* Experience integrating advanced quality evaluation frameworks with downstream
recommendation signals.
* Experience mentoring executive engineers and influencing broader
organizational machine learning strategies.
ABOUT THE JOB:
Google's software engineers develop the next-generation technologies that change
how billions of users connect, explore, and interact with information and one
another. Our products need to handle information at massive scale, and extend
well beyond web search. We're looking for engineers who bring fresh ideas from
all areas, including information retrieval, distributed computing, large-scale
system design, networking and data storage, security, artificial intelligence,
natural language processing, UI design and mobile; the list goes on and is
growing every day. As a software engineer, you will work on a specific project
critical to Google’s needs with opportunities to switch teams and projects as
you and our fast-paced business grow and evolve. We need our engineers to be
versatile, display leadership qualities and be enthusiastic to take on new
problems across the full-stack as we continue to push technology forward.
The team leverages AI-generated content across major surfaces, ensuring optimal
user experience at a massive scale.
In this role, you will
- focus on end-to-end
- personalization and system optimization, integrating feedback loop signals to
- enhance model performance for over 4 billion users.
- In Google Search, we're reimagining what it means to search for information –
- any way and anywhere. To do that, we need to solve complex engineering
- challenges and expand our infrastructure, while maintaining a universally
- accessible and useful experience that people around the world rely on. In
- joining the Search team, you'll have an opportunity to make an impact on
- billions of people globally.Individual pay is determined by factors including
- job-related skills, experience, and relevant education or training.
- US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits
- Learn more about benefits at Google
- [https://www.google.com/about/careers/applications/benefits/].
- RESPONSIBILITIES:
- * Lead the development of advanced AI-generated content (AIGC) recommendation
- frameworks and agentic flows to generate high-quality content for Discover
- and Notifications.
- * Build and implement advanced offline and online quality evaluation frameworks
- for LLMs to ensure content factuality, freshness, and coherence.
- * Conduct advanced quality evaluations and leverage dense recommendation
- signals and feedback to improve the overall performance of the AIGC stack.
- * Drive end-to-end modeling for the personalization flow, focusing heavily on
- inventory quality, retrieval, ranking, user understanding, and budgeting
- predictions.
- * Optimize ML inference and resolve system-level bottlenecks to improve serving
- efficiency for low-latency, high queries-per-second (QPS) global surfaces.
Which skills does this role require?
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- Practice explaining your experience in an interviewRehearse your answers before meeting the hiring team.
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