Job Information
Google Engineering Manager, AI Data, ML Processing and Analysis in Sunnyvale, California
Minimum qualifications:
Bachelor's degree or equivalent practical experience.
8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java).
3 years of experience in a technical leadership role; overseeing projects, with 2 years of experience in a people management, supervision/team leadership role.
Preferred qualifications:
Experience working with Large Language Model (LLM)/GenAI infrastructure.
Understanding of ML research and development workflows.
Ability to work in a fluid and ambiguous environment.
Ability to build the infrastructure ecosystem to support AI researchers and engineers.
Ability to collaborate with other teams across time zones.
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
Our mission is to improve the quality of models that Google releases through its various product offerings by providing tools and services for making faster and easier to reach model quality goals.
AI in the Gemini Era is profoundly data-centric: quality of the data used for training, fine-tuning, or RAG, matters more to the performance of the end product than anything.
The ML, Systems & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google (https://careers.google.com/benefits/) .
Lead a team of Engineers that scale Data Optimization techniques improving the performance and quality of Machine Learning (ML) models.
Work with the Research teams as well as ML practitioners to identify, build and iterate on engineering tools, processing pipelines, data optimization techniques, integration with existing workflows, user interfaces and supporting users adoption.
Work in a fast-evolving field, apply research, and work with users, to further Google’s goal of making AI helpful for everyone.
Help accelerate relationships and iterate in the way GenAI requires us to.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also https://careers.google.com/eeo/ and https://careers.google.com/jobs/dist/legal/OFCCPEEOPost.pdf If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: https://goo.gl/forms/aBt6Pu71i1kzpLHe2.