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Senior Software Engineer, AI/ML, Search Growth

GoogleMountain View, CA, USA

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of experience with one general-purpose systems language (e.g., Java, Kotlin, C++, or Go).
  • 4 years of experience building and maintaining production-grade, latency-sensitive backend or ML systems.
  • 3 years of experience in Deep Learning and ML System Design.
  • 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical field.
  • Experience in Recommendation Systems (Ranking/Prediction), NLP, Reinforcement Learning, or Information Retrieval.
  • Ability to deep-dive into datasets to identify the next high-Return on Investment (ROI) area for technical investment.
  • Ability to balance long-term platform health and engineering with short-term business and growth goals, to address engineering problems at Search scale.
  • Ability to drive technical designs from concept to launch while successfully challenging the status quo.
  • Ability to start in Mountain View within 4 weeks of offer accept.

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 manage information at a 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.

In this role, you will design the new intelligence layer of the Search’s growth ecosystem with a new long-term life-cycle model.In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve engineering issues 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.

The US base salary range for this full-time position is $174,000-$252,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

  • Design and deploy advanced models (e.g., Contextual Bandits, Transformers, Sequence Modeling) to optimize promo inventory by leveraging on multi-headed objective functions that balance growth goals against user annoyance costs.
  • Build systems for training, deploying, and monitoring models. Scale our ML training infrastructure with TensorFlow and JAX.
  • Optimize model architectures for high-throughput, low-latency environments, ensuring the ML models never compromise core Search performance.
  • Drive model performance by testing and ingesting novel signals (including multi-modal embeddings and Large Language Model (LLM)-generated user profiles), designing and executing A/B tests to measure ML-driven feature effectiveness, and iterating quickly based on findings.
  • Build the engine that manages and generates hyper-personalized, multi-turn LLM prompts within the new AI Mode infrastructure.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.

If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.
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