Job Description

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 7 years of experience leading technical project strategy, ML design, and working with industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 5 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.
• 5 years of experience with design and architecture; and testing/launching software products.
• Experience with GenAI techniques or with GenAI-related concepts.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 8 years of experience with data structures and algorithms.
• 5 years of experience in a technical leadership role leading project teams and setting technical direction.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.

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.

In this role, you will be driving technical leadership on high-impact projects in this space, facilitate clarity on goals and timelines, and work with individual contributors in the broader organization to drive the future roadmap for the team. You will also work with partner teams and cross-functional partners who are the generators and consumers of this data, clarifying scope, setting technical direction, and engaging in design and code reviews with the cross-site organization, while also fostering a culture of reliability and production excellence. You will be the advocate for the Infrastructure investments and will drive reliability, scalability, operational excellence for the Infrastructure team, in a very fast paced environment, guiding team members along the way.

Applied AI builds conversational agents deployed at a large scale that achieve very meaningful results in the real world. Some examples include the customer agent built for large call center environments, to fast food ordering handled by our Food AI agent. The team is transforming how enterprises connect with customers through the power of AI. We also offer unique experiences for team members where you get to work directly with the model builders (Google DeepMind / Vertex), learn and work with brilliant AI leaders, and have access to Global 1000 customers via our existing Google Cloud relationships. The opportunity in this space is tremendous.

The US base salary range for this full-time position is $248,000-$349,000 + 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

• Design, develop, test, deploy, maintain, and enhance large scale software solutions.
• Provide technical leadership on high-impact projects.
• Facilitate alignment and clarity across teams on goals, outcomes, and timelines. Influence and coach a distributed team of engineers.
• Drive technical project strategy, lead large-scale ML infrastructure optimization, and oversee the design and implementation of solutions across multiple specialized ML areas.
• Manage project priorities, deadlines, and deliverables.