Bachelor's degree or equivalent practical experience.
5 years of software development experience in one or more programming languages.
3 years of end-to-end Machine Learning experience, including model deployment and evaluation.
3 years of experience building and deploying recommendation systems in production.
Experience developing personalization algorithms for user-specific content delivery.
Experience integrating generative AI tools or LLM interfaces into workflows.
Responsibilities
Research and deploy ML models that maximize exploration ROI using multimodal LLM understanding and causal modeling.
Drive projects from problem formulation to production launches, collaborating with various teams.
Align semantic applicant retrieval and ranking incentives to activate the recommendation flywheel.
Lead discovery for dynamically generated AI content, surfacing breaking news quickly.
Evolve StarSearch into an intelligent gatekeeper for content, enhancing personalization while managing unengaged content.
Benefits
Comprehensive health and wellness programs.
Generous paid time off and parental leave.
Retirement savings plans with company matching.
Opportunities for professional development and training.
Access to cutting-edge technology and tools.
Full Job Description
info_outline X In most instances, this position requires in-person interviews as part of the hiring process.
Minimum qualifications:
Bachelor's degree or equivalent practical experience.
5 years of experience with software development in one or more programming languages.
3 years of experience with end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).
3 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, personalization, search quality, embedding) in production; and experience building architecture.
Experience developing personalization algorithms for user-specific content delivery.
Experience integrating generative AI tools or LLM interfaces into workflows.
Preferred qualifications:
Master's degree or PhD in Computer Science, or related technical field.
5 years of experience with data structures and algorithms.
Experience in Content Exploration/Exploitation (e.g., Bandit systems, Reinforcement Learning) or solving Cold Start problems.
Experience with feed recommendation systems or budgeting systems.
Experience with data pipelines and system design for real-time evaluation.
Responsibilities
Research and deploy ML models that identify content by combining multimodal LLM understanding, uncertainty estimation, and causal modeling to maximize exploration ROI at scale.
Drive projects from problem formulation and experimentation design through model training, real-time serving architecture, and production launches, collaborating closely with Feed Ranking, Content, and Infra teams.
Partner to align semantic applicant retrieval, ranking incentives, and warm-start handoffs so promising new content seamlessly activates the organic recommendation flywheel.
Lead zero-history discovery for Discover's top formats-making dynamically generated AI content (AIGC) a citizen across the stack and surfacing breaking news within minutes of publication.
Evolve StarSearch into the intelligent gatekeeper for Discover's content ecosystem-safely bootstrapping fresh, niche, and creator supply to expand personalization headroom while rapidly pruning unengaged content to keep the serving corpus fresh and efficient.
Google is a multinational technology company that specializes in Internet-related services and products. These include online advertising technologies, search engine, cloud computing, software, and hardware. Google was founded in 1998 by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University. The company has grown tremendously since then and has become one of the most valuable companies in the world. Google's mission is to organize the world's information and make it universally accessible and useful.
