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Research Scientist, ML Efficiency, Google Research

Google

Singapore

On-site

SGD 100,000 - 130,000

Full time

Today
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Job summary

A leading technology firm in Singapore seeks a Research Scientist specializing in ML Efficiency. You will advance algorithms, optimize AI models, and collaborate across teams to enhance computational efficiency in AI systems. Candidates should hold a PhD in Computer Science and possess experience in AI research. This role is pivotal in shaping how next-gen AI models are deployed, working on real-world problems and contributing to the wider research community.

Qualifications

  • PhD degree in Computer Science, a related field, or equivalent practical experience.
  • One or more scientific publication submissions for conferences, journals, or public repositories.

Responsibilities

  • Advance algorithms, sampling techniques, and large-scale optimization.
  • Innovate algorithms and large language model architectures.
  • Improve end-to-end model deployment pipeline.
  • Collaborate with hardware and software teams.
  • Optimize latency, memory bandwidth, and workloads.

Skills

AI research
Deep learning
Machine learning
Cloud computing
Model optimization

Education

PhD degree in Computer Science
Job description
Research Scientist, ML Efficiency, Google Research

Google will be prioritizing applicants who have a current right to work in Singapore, and do not require Google's sponsorship of a visa.

Minimum qualifications:

  • PhD degree in Computer Science, a related field, or equivalent practical experience.
  • One or more scientific publication submissions for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).

Preferred qualifications:

  • Experience in a university or industry labs, with primary emphasis on AI research.
  • Understanding of transformer architecture internals.
  • Ability to drive new research ideas from problem abstraction, designing solution, experimentation, to productionisation in a rapidly shifting landscape.
  • Excellent technical leadership and communication skills to conduct multi‑team cross‑function collaborations.
  • Passionate about deep/machine learning, computational statistics, and applied mathematics.

About The Job

As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large‑scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real‑world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.

As a Research Scientist, you will also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

Google Research Singapore is the very latest addition to the Google Research presence around the globe! Through foundational research, the team will deliver research on algorithmic efficiency, model compression, and inference acceleration, directly impacting how next‑generation AI models will be deployed to billions of people. Google Research is building the next generation of intelligent systems for all Google products. To achieve this, we’re working on projects that utilize the latest computer science techniques developed by skilled software developers and research scientists. Google Research teams collaborate closely with other teams across Google, maintaining the flexibility and versatility required to adapt new projects and foci that meet the demands of the world’s fast‑paced business needs.

Responsibilities

  • Advance algorithms, sampling techniques and large‑scale optimization to make serving and inference of generative AI models more efficient and flexible. This includes model compression, knowledge distillation and quantization strategies.
  • Innovate algorithms and large language model architectures that improve computation efficiency and generalization of training deep learning models.
  • Improve the end‑to‑end model deployment pipeline that includes entirely new formulations of pretraining, instruction tuning, reinforcement learning, thinking and reasoning.
  • Collaborate with hardware and software teams to optimize kernels and inference engines, across different hardware and model architectures.
  • Optimize latency, memory bandwidth, and workloads.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

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