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Google

Staff Software Engineer, AI/ML, Shopping on Search, Commerce, Consumer Shopping Quality

  • Pittsburgh, PA, USA; New York, NY, USAPittsburgh, PA, USA +1 more
  • Posted 5h ago
  • Full-time
  • Staff / Principal

Salary

$207K - $300K

Listed in the posting

Pays more than 70% of 2,745 software engineer listings in USD.

This job
$207k–$300k
Typical
$222k
Most pay
$186k–$266k
Apply on company site

Benefits

  • Equity
  • Bonus

Skills

Agentic AI
AI
Distributed Computing
Generative AI
Machine Learning
Model Deployment
Model Evaluation
Networking
NLP
Recommendation Systems

Nice to have

Reinforcement Learning
Root Cause Analysis

Full job description

Description

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.

With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.

"The Google Commerce team is driving the shift toward agentic commerce—moving beyond static interactions to build intelligent, adaptive shopping experiences. By bringing Gemini into AI Mode in Search and the Gemini app, we're making shopping even more intuitive. Powered by the Google Shopping Graph's 60B+ listings, our team is helping to establish open industry standards like the Universal Commerce Protocol. We're building shopping experiences across Google, including Search, the Gemini app, YouTube, and Ads, to help people discover and buy products from the brands they love and trust on Google.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

  • Drive technical strategy and quality improvements across Shopping GenAI surfaces for visual actionable entities, prioritizing triggering, completeness, and product/offer quality.
  • Design and deploy feature enhancements by utilizing prompt optimization, entity annotation, and novel grounding strategies to improve actionable entity quality.
  • Analyze performance gaps through rigorous loss analysis, collaborating with cross-functional partners to identify and implement solutions across the Gemini & Shopping stack.
  • Contribute to architectural improvements by applying model and infrastructure advances to ensure actionable entities perform reliably and effectively.
  • Collaborate across engineering teams—including Consumer Shopping, Merchant, and GDM—to resolve GenAI feature, Shopping Graph data, policy, and retrieval issues.

Requirements

Minimum qualifications

  • Bachelor’s degree or equivalent practical experience.
  • 8 years of experience in software development.
  • 5 years of experience with ML design and end-to-end machine learning (e.g., model deployment, model evaluation, data processing, debugging).
  • 5 years 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.
  • Experience applying machine learning techniques to search ranking performance and information retrieval systems.
  • Experience building recommendation systems to provide user-specific item or content suggestions.

Preferred qualifications

  • Experience solving open-ended quality problems, identifying systemic gaps, and driving root-cause analysis to resolve them.
  • Experience building user-facing AI features.
  • Experience designing system architecture and AI/ML-powered solutions.
  • Experience defining long-term technical vision and establishing roadmaps for problem spaces.
  • Ability to drive cross-functional alignment across product, engineering, and partner organizations.
  • Ability to move quickly in rapidly changing environments.
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