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Education & Training 🏢 Full Time ⭐️ Terverifikasi

Research Scientist, ML Efficiency, Google Research

Google
Singapore
Estimasi Gaji
World Class Benefits
Live Update
12 Mei 2026
Batas Akhir
12 Mei 2027

Deskripsi Pekerjaan

Join Google Research as a Research Scientist in Machine Learning Efficiency and help shape the future of generative AI. This role offers an unparalleled opportunity to tackle cutting-edge challenges in optimizing and scaling large-scale language models. You'll collaborate with world-class researchers to develop novel algorithms that enhance computational efficiency while maintaining model performance. At Google, you'll work in an environment that values intellectual curiosity and encourages breakthrough thinking. Your contributions will directly impact how AI systems process and generate information, making technology more accessible and sustainable. We provide extensive resources, mentorship, and a collaborative culture where your ideas can flourish. If you're passionate about pushing the boundaries of machine learning efficiency and want your research to reach billions of users, this is the ideal platform to accelerate your impact.

Tanggung Jawab

  • Conduct pioneering research in machine learning efficiency with focus on generative models
  • Design and implement novel optimization techniques for large-scale AI systems
  • Develop algorithms to reduce computational costs while maintaining model performance
  • Collaborate with engineering teams to translate research into production-ready solutions
  • Publish findings in top-tier conferences and contribute to open-source projects
  • Mentor junior researchers and contribute to team research strategy
  • Stay current with emerging AI efficiency methodologies and adapt them to Google's infrastructure

Kualifikasi

  • PhD in Computer Science, Machine Learning, or related field (or equivalent experience)
  • Strong background in deep learning architectures and generative models
  • Expertise in optimization techniques for neural networks (quantization, pruning, distillation)
  • Proficiency in Python/C++ and ML frameworks (TensorFlow, PyTorch)
  • Demonstrated track record of peer-reviewed publications in ML/AI conferences
  • Experience with large-scale distributed computing systems
  • Exceptional analytical and problem-solving abilities
  • Excellent communication skills for technical and non-technical audiences

Keahlian yang Dibutuhkan

Machine Learning Deep Learning Generative AI Optimization Algorithms Python C++ TensorFlow PyTorch Distributed Systems Research Model Efficiency

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