Description

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 5 years of experience programming in Python or C .
• 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 one or more of the following: reinforcement learning (e.g., sequential decision making), multimodal Machine Learning, ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging), or specialization in another ML field.
• Experience with experiment analysis.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
• 5 years of experience with data structures and algorithms.
• 1 year of experience in a technical leadership role.
• Experience leading and optimizing industry-scale machine learning infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• Experience developing accessible technologies.

About the jobGoogle'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 manage information at a 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.

As a part of the team that builds the AI-powered automation at the heart of Google Ads, you will contribute to Keywordless Search Ads, a technology powering multiple key products, including Dynamic Search Ads, AI Max, Performance Max, and Smart Campaigns, which help advertisers connect with users effectively and efficiently. You will play a key role in executing an ambitious plan to significantly grow the impact of automated targeting in Search ads in the coming years, with cross-team collaboration opportunities within Search Ads Quality such as with Google DeepMind and Research.

In this role, you will need to be passionate about applied machine learning, distributed systems, and building products that help people.Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We're made up of multiple teams, building Google's Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.

The US base salary range for this full-time position is $166,000-$244,000 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.

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.
• Manage open-ended engineering problems related to ad relevance, query understanding, and large-scale system optimization.
• Develop and deploy new ML/Large Language Model (LLM) models to make direct impact to Google, advertisers and users.

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Requisition #: 82851935043887814

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