About the position
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. You will be involved in the full machine learning model lifecycle, from design and training to deployment and serving models in production at scale. You will innovate while collaborating with other teams to test and implement the latest technologies in models. You will be involved at a high level in the infrastructure that supports serving these models at scale on Search traffic. 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
- Write and test product or system development code.
- Contribute to code health, automation, and alerting systems to ensure model stability and performance.
- Improve and simplify models through advanced machine learning techniques, improving quality, stability, and efficiency across the entire model lifecycle—from concept to deployment.
- Solve machine learning related problems by designing, running, and analyzing experiments using statistical methods.
Requirements
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development in C++ and Python, and with data structures/algorithms.
- 3 years of experience testing, maintaining, or launching software products.
- 1 year of experience with software design and architecture.
- 3 years of experience with one or more of the following: Speech/audio, reinforcement learning, ML infrastructure, or specialization in another ML field.
- 3 years of experience with ML infrastructure.
Nice-to-haves
- Master's degree or PhD in Computer Science or related technical field.
- 1 year of experience in a technical leadership role.
- Experience developing accessible technologies.
- Experience with Machine Learning (ML) algorithms and tools (e.g., TensorFlow, Pytorch, Keras).
Benefits
- Base salary range of $166,000-$244,000 + bonus + equity + benefits.
