Staff Software Engineer, AI/ML, YouTube Ads

Google Inc.; Mountain View (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google Inc. is looking for a Staff Software Engineer specializing in AI and Machine Learning for YouTube Ads in Mountain View, CA. This role involves leading the development of advanced machine learning models and managing the integration of these technologies in advertising systems. Applicants should have a Bachelor's degree and substantial experience in software development, with a strong preference for those holding a Master's degree or PhD. The position offers a competitive salary range of $207,000 to $300,000, plus bonuses and benefits.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience testing and launching software products, and 3 years of experience with software design and architecture.

Responsibilities

• Lead the end-to-end development of novel machine learning models.
• Build and scale end-to-end machine learning pipelines.
• Explore, implement, and integrate with generative models.
• Apply deep learning and reinforcement learning to optimize creative composition.
• Contribute to the architecture of centralized services for unifying asset attributes.

Job description

Staff Software Engineer, AI/ML, YouTube Ads

YouTube, Mountain View, CA, USA

Required qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience testing and launching software products, and 3 years of experience with software design and architecture.

Preferred qualifications

• Master's degree or PhD in Computer Science, Machine Learning, or a related technical field.
• 8 years of experience in data structures and algorithms.
• 5 years of experience building and productionizing machine learning models, with experience in deep learning or reinforcement learning.
• Experience with machine learning frameworks like TensorFlow and JAX, production machine learning platforms such as TensorFlow Extended and AdBrain, and generative models and their applications.
• Proficiency in designing, running, and analyzing large-scale online experiments (A/B tests).
• Familiarity with online advertising systems, creative optimization, personalization, or recommender systems.

Responsibilities

• Lead the end-to-end development of novel machine learning models, incorporating techniques like deep learning, reinforcement learning, and generative artificial intelligence, from concept to production.
• Build and scale end-to-end machine learning pipelines for model training, inference, and integration with high-throughput ad serving systems.
• Explore, implement, and integrate with generative models for text, image, and video adaptations within ads.
• Apply deep learning and reinforcement learning to understand asset value and optimize creative composition while developing metrics and algorithms to ensure creative freshness and efficient exploration.
• Contribute to the architecture of centralized services for unifying asset attributes and model-driven insights across different applications, collaborating with infrastructure and serving teams to power creative optimization.

The US base salary range for this full‑time position is $207,000–$300,000 plus bonus, equity, and benefits. Salary ranges are determined by role, level, and location. Individual pay is based on job‑related skills, experience, and relevant education or training.

Google is a proud equal‑opportunity and affirmative‑action employer. We are committed to building a workforce that is representative of the users we serve and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity or expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law. See also Google's EEO Policy, the Belonging at Google program, and How we hire.