Senior Software Engineer, AI/ML

Google•Mountain View, CA

1d•$174,000 - $252,000

About The Position

Google software engineers develop next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Google products handle information at massive scale and extend beyond web search, across areas including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design, and mobile. In this role, you will work on a project critical to Google’s needs, with opportunities to switch teams and projects as the business evolves. Engineers are expected to be versatile, demonstrate leadership qualities, and take on problems across the full stack. The position focuses on translating research into product improvements in generative AI, developing and evaluating ML models using large-scale user-log data, building data-processing infrastructure, and applying ML models to improve Google products.

Requirements

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 one or more of the following: large language models, natural language processing, human-computer interaction, or computer vision.
3 years of experience with ML infrastructure, such as model deployment, model evaluation, optimization, data processing, or debugging.

Nice To Haves

Master’s degree or PhD in Computer Science or a related technical field.
5 years of experience with data structures and algorithms.
Applied ML skills in LLMs and NLP; experience with TensorFlow, Python, and building and launching ML models.
Strong analytical abilities for data analysis.

Responsibilities

Collaborate with peers and stakeholders through design and code reviews to ensure best practices in style guidelines, code checking, accuracy, testability, and efficiency.
Translate research into product impact and improvements in generative AI quality.
Develop and evaluate new ML models using large-scale user-log data; build infrastructure for processing large-scale data and perform statistical analysis to derive actionable insights.
Drive applications of ML models to improve quality for various core Google products.
Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.