Senior Software Engineer, Managed AI/ML Infrastructure

Google•Apply•Published 19 hours ago•First seen 18 hours ago

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.

Virtual Machines (VMs) running in Google Cloud are the backbone of thousands of systems that the comfort and quality of our lives depend on from online shopping systems, through databases and file servers, data analysis pipelines to banking systems. They all rely on computational power, network connectivity and persistent storage delivered through our VMs.

In this role, you will be building solutions for managing the life-cycle of a global population of Virtual Machines in Google Cloud, shape the market, and you will have an opportunity to become a partner in conversations with customers you can think of in the cloud business.

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.
Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.

Minimum qualifications:

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: 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.
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 or related technical field.
5 years of experience with data structures and algorithms.
1 year of experience in a technical leadership role.
Experience developing accessible technologies.