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Senior Software Engineer, AI/ML, Geo and Gemini App

Google
15 hours ago
Full-time
On-site
New York City, NY
$174,000 - $253,000 USD yearly

JobsCloseBy Editorial Insights

Google seeks a Senior Software Engineer, AI/ML for the Geo and Gemini App in New York City, full-time onsite, to build scalable C++ backend components in distributed systems and advance generative AI features. Required: bachelor’s or equivalent, 5 years in backend C++ within distributed systems, 3 years testing or launching software, and 1 year in design or architecture; plus experience with Large Language Models, prompt engineering, retrieval augmented generation, and model quality optimization. Preferred: 5 years in data structures and algorithms, leadership, ML frameworks, data analysis, experimental design and A/B testing, and comfort with fast paced, startup-like environments. Responsibilities include context engineering pipelines, evaluation, and cross-functional collaboration to improve personalization. Pay US 174k-253k plus 15% bonus, equity, benefits. To apply, highlight concrete LLM/GenAI projects, RAG, loss analysis, leadership, and measurable impacts; show you can thrive onsite in NYC and collaborate across teams.

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of experience developing C++ backend infrastructure components within distributed systems.
  • 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  • Experience with Large Language Models (LLMs) and Generative AI concepts (e.g., prompt engineering, retrieval-augmented generation (RAG)).
  • Experience with model quality optimization using methods such as loss analysis or quality hillclimbing.

Preferred qualifications:

  • 5 years of experience with data structures and algorithms.
  • 1 year of experience in a technical leadership role.
  • Experience working in fast-paced, startup-like environments with rapidly changing priorities.
  • Experience in data analysis, experimental design, and statistical methods.
  • Experience with common ML frameworks (e.g., TensorFlow, JAX, PyTorch).
  • Familiarity with user metrics logging and A/B testing for software products.

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.

The Geo team is focused on building the most accurate, comprehensive, and useful maps for our users, through products like Maps, Earth, Street View, Google Maps Platform, and more. Every month, more than a billion people rely on Maps services to explore the world and navigate their daily lives.

The Geo team also enables developers to use the power of Google Maps platforms to enhance their apps and websites. As they plot a course for the future of mapping, they are solving complex computer science problems, designing beautiful and intuitive product experiences, and improving our understanding of the real world.

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

US: $174000 - $253000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Build context engineering pipelines, agentic workflows with tool usage, and robust evaluation frameworks.
  • Analyze model behavior, creating high-quality evaluation datasets to identify weaknesses and guide performance improvements.
  • Enhance serving and evaluation infrastructure to power new user-facing features.
  • Act as a technical bridge between engineering, product, UX, and research teams to translate user needs into valuable features.
  • Analyze user metrics and model outputs to enhance personalization and overall system helpfulness.