Minimum qualifications:

Bachelor’s degree or equivalent practical experience.
2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
1 year 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.
1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Preferred qualifications:

Master's degree or PhD in Computer Science or related technical field.
2 years of experience with data structures or algorithms.
Experience developing accessible technologies.
Experience in machine learning or adjacent fields (e.g. information retrieval, natural language processing, computer vision).

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.

We are looking for a strong applied artificial intelligence/machine learning (AI/ML) and quality software engineer to join this exciting, fast evolving space, to help our team rapidly improve products. This role provides the unique opportunity to work on a highly visible and business critical project in a changing and fun environment, collaborating across product areas like Search, YouTube, Gemini and Google DeepMind.

Learning is the ongoing quest for understanding, and we made it our mission more than 20 years ago to organize the world’s information to make it universally accessible and useful. The learning landscape is changing, and the Learning and Education team's mission is to help everyone in the world learn anything in the world. We provide the information, tools, and services that help people gain knowledge, fuel curiosity, and prepare for what’s next. We focus our work to add the most value for users to enable learning for school, work, and life. We believe everyone can and should have access to quality learning experiences to reach their full potential.

The US base salary range for this full-time position is $141,000-$202,000 + 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

Implement solutions in one or more specialized machine learning (ML) areas, utilize ML infrastructure, and contribute to model optimization and data processing.
Train machine learning models and optimize quality through training data, prompts, reinforcement learning (RL), hyperparameters, or architecture changes. Work with team leaders and product managers to define quality goals.
Generate new ideas for product improvements, partnering with engineers from Search / LearnX, and researchers from DeepMind.
Evaluate trained models through autoraters, human evaluation and live experiments. Define and refine evaluation methods as necessary.
Develop in a changing and ambiguous environment, embracing an iterative approach to manage quality issues effectively.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .

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