Senior Software Engineer, AI/ML, Ads Bidding

Google; New York (NY); On-site; USD 166,000 - 244,000; Full time

Job summary

Google is seeking a Senior Software Engineer specializing in AI/ML for Ads bidding in New York, NY. You will design, train, and deploy models that predict advertiser interactions and optimize auto-bidding, working across research and production teams.

The role emphasizes scalable ML systems, collaboration, and building capabilities for large-scale Ads products. Compensation includes base salary, bonus, equity, and benefits.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in C++ or Python.
• 3 years of experience with deep learning, recommendations, RL, ML infra, or related ML field.
• 3 years of experience testing, maintaining, or launching software products, and 1 year with design/architecture.
• 3 years of experience with ML infrastructure (model deployment/evaluation/processing).
• Master’s or PhD in CS/Math or related field (preferred).
• 5 years of experience with data structures/algorithms (preferred).
• 1 year in a technical leadership role (preferred).
• Experience developing accessible technologies (preferred).

Responsibilities

• Write and test product or system development code.
• Collaborate through design and code reviews to ensure best practices.
• Improve and simplify models through advanced ML techniques.
• Innovate and iterate on ML model design across the lifecycle.
• Solve complex ML problems by designing, running, and analyzing experiments.

Skills

C++/Python development

ML fundamentals

Mentoring

Education

Bachelor’s degree or equivalent practical experience

Master’s or PhD (preferred)

Job description

Senior Software Engineer, AI/ML, Ads Bidding

corporate_fareGoogle

placeNew York, NY, USA

Mid

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 5 years of experience with software development in C++ or Python.
• 3 years of experience with one or more of the following: deep learning, recommendations, reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• 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).

Preferred qualifications:

• Master's degree or PhD in Computer Science, Mathematics, or a related Science or Technical field.
• 5 years of experience with data structures/algorithms.
• 1 year of experience in a technical leadership role.
  
• Experience developing accessible technologies.
  

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.

We build and maintain machine learning models using AI and ML techniques to predict user interactions on Search Ads. These models are key in setting advertisers' bids, with the goal of improving both satisfaction and Return on Investment (ROI) for Search Ads advertisers using Auto-bidding products. By optimizing towards advertisers' objectives, Auto-bidding products drive Google's global Ads business.

In this role, you will be involved in the full machine learning model lifecycle, from design and training to deployment and serving models in production at the scale of Search Ads. You will innovate while collaborating with other teams, including research, to test and implement the latest technologies in our models. Additionally, you'll also be involved at high level infrastructure that supports serving these models at scale.

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).
  
• Work on improving and simplifying models through advanced machine learning techniques.
  
• Innovate and iterate on machine learning model design, improving quality, stability, and efficiency across the entire model lifecycle—from concept to deployment.
  
• Solve complex machine learning related problems by designing, running, and analyzing experiments using analytical and statistical methods.
  

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Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

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