Software Engineer III, AI/ML, Proxybidder ML

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’s machine learning models drive the global Ads business, serving billions of users and generating significant business.

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.

Responsibilities

• Develop and maintain machine learning models using advanced AI techniques to predict user interactions and optimize advertiser Return on Investment (ROI).
• Innovate on machine learning model design to improve quality, stability, and efficiency throughout the entire model lifecycle.
• Analyze experiments using statistical methods to solve complex machine learning problems and improve model generalization.
• Enhance model health and stability by contributing to code health, automation, and alerting systems.
• Collaborate with Research and Infrastructure teams to test and implement the latest technologies in production environments.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 2 years of experience with software development in Python and C++ programming languages, or 1 year of experience with an advanced degree.
• 2 years of experience applying mathematical modeling, numerical analysis, or statistical methods to solve engineering or scientific problems.
• 1 year of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
  
• 1 year 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 or related technical fields.
  
• Experience with machine learning, statistical analysis, applied math, or operation research in the industry or in the academic sector.
• Experience productionizing machine learning systems or designing experiments.
• Experience with Google Ads systems or specialized ML tools such as TensorFlow, Keras, or TFX.
• Ability to to write high quality and low latency code/models that can train on and serve on every query.