AI/ML Senior Software Engineer, Data Optimization and Platform

AI/ML Senior Software Engineer, Data Optimization and Platform Overview

This role sits within Google Cloud’s engineering organization and focuses on improving how machine learning teams use data to reach model quality faster. The work is centered on data optimization and platform tooling for the Gemini era, where the quality of training, fine-tuning, and retrieval-augmented generation data has an outsized effect on model performance. The team’s mission is to make it easier for a broad set of users to apply data optimization methods through integrated tools and platforms, automatically run structured comparisons to show what works best for a given use case, and surface practical guidance for further improvement.

You would be joining a team that collaborates closely with product groups across Google. The broader ML, Systems, and Cloud AI organization builds and operates the hardware, software, machine learning, and systems infrastructure behind Google services and Google Cloud. That includes work spanning Search, YouTube, Google Cloud, and Vertex AI, with a strong emphasis on security, efficiency, and reliability at global scale.

What you would do

• Take data optimization techniques, including methods developed in Google Research, and scale them so they improve model performance and model quality across multiple product areas.
• Help shape the technical direction of the data platforms used for model tuning, influencing how these platforms evolve across different teams and use cases.
• Build and maintain technical relationships with several product areas so strategy and engineering direction are aligned.
• Reuse and adapt research assets and techniques to increase the speed at which teams can tune models, including teams working on Bard and other Gemini fine-tuning efforts.
• Partner with research teams and machine learning practitioners to design, implement, and iterate on internal engineering tools, data-processing pipelines, optimization methods, workflow integrations, user-facing interfaces, and adoption support.
• Work directly with users to apply research in practical ways and help Google move toward making AI broadly helpful.

What the role is looking for

• A bachelor’s degree or equivalent hands-on experience.
• At least five years of experience using Python with strong knowledge of data structures and algorithms.
• At least three years of experience in one or more machine learning areas such as speech and audio, reinforcement learning, ML infrastructure, or another specialized ML domain.
• At least three years of experience in ML infrastructure work, including deployment, evaluation, data processing, and debugging.
• Practical experience with data analysis, data optimization, and data evaluation.
• Ability to work in English, which Google states is required for all roles unless the posting says otherwise.

Preferred background

• A master’s degree or PhD in computer science or a closely related technical discipline.
• Five years of experience in a complex organization with many teams and dependencies.
• Experience working with generative AI.
• Experience building or improving data optimization systems and data platforms.
• Experience taking research work into production environments.

Additional context

The position is described as a mid-level role, meaning it is suited to someone with enough experience to drive progress, solve problems independently, and mentor less experienced engineers. The posting also notes that Google is a global company and that English proficiency is required to support collaboration and communication across regions.

Google states that it is an equal opportunity and affirmative action employer and that it is committed to building a workforce that reflects the users it serves. The company says it provides equal employment opportunity regardless of protected characteristics such as race, religion, gender, sexual orientation, gender identity or expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy-related conditions, or other legally protected bases. It also references its EEO policy, workplace discrimination rights, belonging resources, and hiring information.

If you need an accommodation during the application process, Google asks that you complete its accommodations form for applicants.

The posting also says Google does not accept agency resumes and asks recruitment agencies not to forward resumes to its jobs alias, employees, or other locations. It further explains that unsolicited resumes do not create any fee obligation for Google.

On compensation-related equity, the posting says any Alphabet equity grant is discretionary, governed by the relevant stock plan and grant agreement, and subject to approval by the board or its delegate. It also states that such grants are not guaranteed and do not affect statutory payments.

How to apply

The page indicates that applicants should use the Google Careers application process for this role. It also notes that information collected through a Google Careers profile and any submitted application is handled under Google’s Applicant and Candidate Privacy Policy.

Degree Requirement: Bachelor’s

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