Machine Learning Engineer, Large Language Models, Personal AI Full-time

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development, with data structures or algorithms.
• 8 years of experience in coding with one or more programming languages (e.g., c or python).
• 5 years of experience in testing, and launching software products, and 3 years of experience with software design and architecture.
• Experience in the domain area of generative AI, large language models, or machine learning.
• Experience in the domain area of Generative AI, large language models, or machine learning.

Preferred qualifications:

• Master’s degree or Phd in Engineering, Computer Science, or a related technical field.
• 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.

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.

With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.

Pixel AI is building a AI Agent on Pixel that is personal, private and on device. We believe technology has emerged Large Language Models to enable such an agent and create a differentiating and transformative experience, especially with Pixel’s unique take on hardware engineer (e.g., Tensor chip), Support Widget and AI.

In this role, you will work on many omity problems, such as, on device large language model, AI agent’s interaction with tools or APIs, private and personalized AI, etc. You will be responsible for developing machine learning system and models. This includes data collection design, data engineering, feature engineering, model training, and model evaluation.

The Google Pixel team focuses on designing and delivering the world’s most helpful mobile experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google’s artificial intelligence, software, and hardware to build global smartphones and create transformative experiences for users across the world.

The US base salary range for this full-time position is $189,000-$284,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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

• Provide technical leadership on omit projects.
• Influence and coach a distributed team of engineers.
• Facilitate alignment and clarity across teams on goals, outcomes, and timelines.
• Manage project priorities, deadlines, and deliverables.
• Design, develop, test, deploy, maintain, and enhance software solutions.