Senior Software Engineer, Machine Learning, Discover Interest Modeling

About the role

MINIMUM QUALIFICATIONS:

• Bachelor’s degree or equivalent practical experience.

• 5 years of experience with machine learning algorithms and tools (e.g.,

TensorFlow), Recommender Systems, deep learning, or personalization.

• 3 years of experience testing, maintaining, or launching software products,

and 1 year of experience with software design and architecture.

• 3 years of experience building and deploying recommendation systems models

(retrieval, prediction, ranking, personalization, search quality, embedding)

in production, and experience building architecture.

• Experience with deep learning architectures and related algorithms (e.g.,

Transformers).

PREFERRED QUALIFICATIONS:

• Master's degree or PhD in Computer Science or related technical field.

• 5 years of experience with data structures and algorithms.
• 1 year of experience in a technical leadership role.

• Experience developing accessible technologies.

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.

Discover is Google's personalized interest feed. With daily active users, it is

one of the largest feed recommendation products in the world.

In this role, the profile captures each person's long-term interests, favorite

creators and in-the-moment intent. As these models drive recommendations a day,

among the most important personalization signals in downstream ranking, and feed

personalization across Google.

Every Discover feed starts with us, from a constantly refreshing corpus of

articles, videos, creator posts and AI-generated content, our retrieval and

pre-ranking stack selects the applicants most relevant to each person.

In Google Search, we're reimagining what it means to search for information –

any way and anywhere. To do that, we need to solve complex engineering

challenges and expand our infrastructure, while maintaining a universally

accessible and useful experience that people around the world rely on. In

joining the Search team, you'll have an opportunity to make an impact on

billions of people globally.

Individual pay is determined by factors including job-related skills,

experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google

[https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES:

• Add predictive modeling of the interests and creators a user will engage with

next. Train with multi-objective goals (engagement, satisfaction).

• Redesign the interest vocabulary for much higher precision, and evaluate

learned alternatives to today's interest vocab.

• Build deep, sequence-based token models that learn from long user activity

histories across Google products.

• Build offline evaluation that predicts online results (profile-quality

autoraters, retrieval and ranking metrics), and run well-sliced live

experiments.

• Design a shared token description, feature set, and training objectives

across token types.