Staff Applied ML Software Engineer, Recommendations, YouTube

Google•San Bruno, CA

2d•$207,000 - $300,000

About The Position

Google software engineers build technologies that help billions of users connect, explore, and interact with information. This role is on YouTube’s recommendations team, where recommendation systems retrieve and rank videos based on viewer context and preferences. The recommendation stack continues to evolve with advances in machine learning, including transformers, foundation models, and Gemini models. The engineer will apply deep machine-learning expertise, particularly in recommendations, to develop advanced algorithms and optimization techniques. The role also involves technical leadership on high-impact projects, guiding recommendation-system design and implementation, optimizing ML infrastructure, and shaping model architecture. The position requires research experience, demonstrated through ML or related-field publications; the description also notes a PhD in ML or related technical fields as a form of research background. Google describes its work environment as collaborative and fast-paced, with opportunities to work across teams and projects as business needs evolve. Individual pay depends on job-related skills, experience, and relevant education or training. The stated U.S. compensation is $207,000–$300,000, plus a 20% bonus target, equity, and benefits.

Requirements

Bachelor's degree in Computer Science or a related field, or equivalent practical experience.
8 years of experience in software development.
5 years of experience building and deploying recommendation-system models in production, including retrieval, prediction, ranking, or embedding models, and experience building architecture in different modeling domains.
5 years of experience with ML design and ML infrastructure, such as model deployment, model evaluation, data processing, debugging, or fine-tuning.
3 years of experience in Applied Machine Learning.
Experience with publications in ML or a related field.
Deep knowledge of ML technologies, especially recommendation systems, and prior ML experience.

Nice To Haves

Master's degree or PhD in Computer Science or a related 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.
Research background through a PhD in ML or publications in ML or related technical fields, including Physics, Math, Operations Research, or Optimization.

Responsibilities

Provide technical leadership on high-impact projects and manage project priorities, deadlines, and deliverables.
Facilitate alignment and clarity across teams on goals, outcomes, and timelines.
Influence and coach a distributed team of engineers.
Lead the design and implementation of recommendation systems, optimize ML infrastructure, and guide model-architecture development.
Analyze data, draw conclusions from logs, and use machine learning to improve the product.