Staff Software Engineer, AI/ML, GenAI

Minimum Qualifications:

• Bachelor's degree in Electrical Engineering, Computer Science, with an emphasis on ML/AI, a relevant technical field, 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 leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 2 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).

Preferred Qualifications:

• Experience as a technical lead for a small team (e.g., 3-6 people).
• Experience with agentic systems, ML domains such as reinforcement learning, image analysis or advanced statistics.
• Strong understanding of the software development lifecycle and best practices.
• Familiarity with Android or mobile software development concepts.
• Demonstrated ability in establishing and tracking meaningful metrics for ML system performance and reliability.
• A strong grasp of machine learning fundamentals with a passion for coaching and mentoring junior team members.

About The Job

We are a small, dynamic team at the forefront of generative AI. Our mission is to automate device operations across a variety of form factors (including phones, laptops, and tablets) and to derive insights from acquired data. Inspired by recent AI advancements, we aim to build agents capable of operating devices, at scale and with high efficiency and accuracy. We foster a collaborative environment where team members can learn from each other and contribute together.

ChromeOS delivers quality computing at scale to provide universal and unfettered access to information, entertainment, and tools. Our mission is to empower anyone to create and access information freely through fast, secure, simple, and intelligent computing.

Responsibilities

• Design, develop, deploy, and maintain scalable machine learning systems for our device automation and app analysis platforms, with a focus on generative and agentic AI.
• Enhance and refine our AI-powered agents to improve their understanding and execution capabilities across diverse form factors.
• Define, establish, and track Key Performance Indicators (KPIs) and metrics to rigorously evaluate and iterate on the performance, quality, and reliability of our ML systems.
• Collaborate closely with other engineers in a fast-paced environment.
• Provide technical leadership, and mentor junior team members on machine learning best practices, fostering their growth and development.