AI/ML Engineer for Shopping Relevance Models

Google LLC; Mountain View (CA); On-site; USD 147,000 - 210,000; Full time

Job summary

Google's Shopping Relevance Models team seeks a Software Engineer to build and deploy ML models that predict ad relevance and improve matches between queries and product listings. You will work on retrieval and ads ranking to influence which ads are shown and how they are priced.

The role requires a Bachelor's degree or equivalent, 2 years Python or C++, 1 year end-to-end ML experience, and familiarity with RL or ML infra, ranking, or recommendations.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 2 years of experience programming in Python or C++.
• 1 year of experience with end to end machine learning (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• 1 year of experience with one or more of the following: reinforcement learning (e.g., sequential decision making), ML infrastructure, Ranking, or Recommendations.

Responsibilities

• Write product or system development code.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
• Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.
• Train machine learning models and explore model features, architectures, and hyperparameters in order to continuously improve model accuracy.

Skills

Python

C++

End-to-end ML

RL / ML infra

Education

Bachelor's degree or equivalent practical experience

Job description

Google's Shopping Relevance Models team seeks a Software Engineer to build and deploy ML models that predict ad relevance and improve matches between queries and product listings. You will work on retrieval and ads ranking to influence which ads are shown and how they are priced.

The role requires a Bachelor's degree or equivalent, 2 years Python or C++, 1 year end-to-end ML experience, and familiarity with RL or ML infra, ranking, or recommendations.