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X In most instances, this position requires in-person interviews as part of the hiring process.Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
Mountain View, CA, USA; Pittsburgh, PA, USA.
Minimum qualifications: - Bachelor's degree or equivalent practical experience.
- 8 years of experience programming in Python or C .
- 5 years of experience testing, and launching software products.
- 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 3 years of experience with software design and architecture.
- 2 years of experience with GenAI techniques (e.g., large language models, multi-modal, large vision models) or with GenAI-related concepts (e.g., 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 and algorithms.
- 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
About the jobWith your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.
Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $300000 (USD) 20% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - Work across many different aspects of machine learning infrastructure and modeling.
- Change infrastructure (training and serving) to support new modeling techniques and products.
- Prototype new infrastructure, automation, workflows, and tooling. Analyze and debug performance, and make improvements.
- Improve robustness, reliability, and usability of infrastructure. Collaborate closely with other members of our team and partners to build systems that take advantage of and integrate seamlessly across our ecosystem.
- Engage with modeling teams to explore pain points and novel use cases. Research emerging technology and make trade-off decisions on immediate wins vs longer-term stability.
