Senior Software Engineer, AI/ML, Youtube Ads Creative Optimization

Senior Software Engineer, AI/ML, Youtube Ads Creative Optimization Share Senior Software Engineer, AI/ML, Youtube Ads Creative Optimization _corporate_fare_ YouTube _place_ Mountain View, CA, USA **Mid** Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area. Share Senior Software Engineer, AI/ML, Youtube Ads Creative Optimization _info_outline_ XIn most instances, this position requires in-person interviews as part of the hiring process. **Minimum qualifications:**

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• 3 years of experience building and productionizing machine learning models, with experience in deep learning or reinforcement learning.

**Preferred qualifications:**

• Master's degree or PhD in Computer Science or a related technical field.
• 5 years of experience with data structures and algorithms.
• 1 year of experience in a technical leadership role.
• Experience with ML frameworks (e.g., TensorFlow, JAX) and production ML platforms (e.g., TFX, AdBrain).
• Experience with large-scale data processing and distributed systems.
• Familiarity with online advertising systems, creative optimization, personalization, or recommender systems.

**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. 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: $174000 - $252000 (USD) + 15% bonus target + equity + benefits Learn more aboutbenefits at Google ( . **Responsibilities**

• Write and test product or system development code.
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency,)
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
• Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.

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