Staff Software Engineer, On-Device Machine Learning

Google•Apply•Published 2 days ago•First seen 2 days 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.

In this role you will provide strategic leadership for the technical direction of On-Device Machine Learning and Generative AI at Google. This role demands an individual who can grow on ambiguity, taking complex, open-ended problems such as the massive-scale deployment of Large Language Models on mobile hardware and making them tractable for the organization. You will lead efforts across multiple teams and stakeholders to define the "well-lit paths" for the next generation of on-device ML innovation. You will have a deep understanding of GenAI workflows and work up and down the stack with engineers on the On-Device Machine Learning (ODML) and hardware teams to define and build new developer tools to serve new LLM needs.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

The US base salary range for this full-time position is $197,000-$291,000 + 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

Create roadmaps for developer-facing APIs, SDKs, and tools, ensuring they meet the evolving needs of LLM workflows.
Solve technically challenging problems that exceed the scope of a generalist Software Engineers, specifically around optimizing GenAI performance across heterogeneous hardware (CPUs, GPUs, and EdgeTPUs).
Guide the team in designing resilient and robust systems, proactively anticipating scaling bottlenecks or shifts in usage as LLMs become increasingly complex.
Coordinate efforts across multiple groups, including Android ML, ML Compiler, and DeepMind, to co-design performance and evaluation workflows.
Provide technical mentorship, and implement new practices that address team needs and increase the velocity of your teammates.

Minimum qualifications:

Bachelor’s degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
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 ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

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.
3 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.
Experience in GenAI end-to-end workflow.
Experience with mobile app development experience and familiarity with iOS/Android build/testing system.