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Salary
≈ $42k – $87k per year (Estimated)
Location
In office (Singapore)
Seniority
Middle · 1+ year exp

Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Oct 16, 2026. Google scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Google is an American technology company founded in 1998 by Larry Page and Sergey Brin and now the principal subsidiary of Alphabet, headquartered in Mountain View, California. It operates the world's dominant search engine and the advertising system built around it, along with YouTube, Android, Chrome, Gmail, Maps, Workspace and Google Cloud, reaching billions of users across nearly every internet-connected market. The company designs its own silicon in the Tensor Processing Unit line, develops the Gemini foundation models through Google DeepMind, and derives most of its revenue from advertising while cloud has become its fastest growing segment.

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 Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.

Responsibilities

  • Design, build, and scale content safety systems including classifiers, vector databases, and multimodal models to protect business-critical products and GenAI experiences.
  • Develop and maintain production-grade distributed systems and content processing pipelines optimized for high throughput and reliability across server-side and on-device environments.
  • Train, evaluate, and productionize models, incorporating feedback loops and automation to continuously improve model quality and performance.
  • Implement agentic workflows and advanced heuristics for deep threat understanding, enabling the proactive detection of complex abuse patterns.
  • Drive agile engineering efforts to identify and mitigate novel abuse patterns, ensuring Google’s products remain engaged and safe in a shifting threat landscape.

Qualifications

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 1 years of experience with software programming in Python, Java, or C++.
  • 1 year of experience in a core ML domain, such as Generative AI, Natural Language Processing (NLP), computer vision, speech/audio, reinforcement learning, recommendation systems, or ML infrastructure.
  • 1 year of experience with ML infrastructure (e.g., model training, model inference, model deployment, model evaluation, optimization, data processing, debugging).

Preferred qualifications:

  • Experience managing safety for User-Generated Content or GenAI products, with a deep understanding of adversarial incentives, abuse vectors, and distribution dynamics like virality.
  • Experience in safety-adjacent domains, including factuality, product policy, or broader Responsible AI frameworks.
  • Experience designing and deploying global-scale defensive architectures and pipelines capable of meeting rigorous Service Level Objectives (SLOs).
  • Demonstrated accountability for managing technical debt, reducing bug counts, and mitigating SLO breaches to maintain high operational standards.
  • Understanding of Machine Learning and Large Language Model (LLM) architecture, specifically transformers, activations, and the requirements for efficient, large-scale training and deployment.
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