The role
From Google's own posting.
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.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
The User-AI Flywheel team in Search Intelligence builds new AI-driven tools for automatic self-improvement, and feedback-driven model training and automated evaluations of all Google Search features and its ecosystem, including AI Mode and AI Overviews.
You will build products that impact billions of users while leading technical contributions in a team to make it happen. The role will benefit from a creative problem solver, focused on innovation, and willing to take calculated risks.
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 .
Advocate the development of modeling, tuning, and optimization techniques to support large language model (LLM) performance, quality, and capabilities.
Guide the design and implementation of user-signal-driven improvements of LLMs to address known loss patterns and response quality behaviors.
Partner with experts from Google Research and DeepMind to advance LLM technologies and integrate them into groundbreaking products.
Demonstrate exceptional teamwork, sharing your expertise in system design, machine learning modeling, and coding practices tailored to the LLM domain.
Cultivate relationships with stakeholders across the organization to collaboratively define and execute LLM initiatives.
Minimum qualifications:
Bachelor's degree or equivalent practical experience.
8 years of experience in software development.
7 years of experience leading technical project strategy, ML design, and optimizing industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
5 years of experience with design and architecture; and testing/launching software products.
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).
Preferred qualifications:
Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
8 years of experience with data structures/algorithms.
5 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.
Bachelor's degree or equivalent practical experience.
8 years of experience in software development.
7 years of experience leading technical project strategy, ML design, and optimizing industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
5 years of experience with design and architecture; and testing/launching software products.
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).