Staff Research Scientist, ML Efficiency, Google Research

Google; Singapore; On-site; SGD 90,000 - 120,000; Full time

Job summary

A leading technology firm is seeking a Staff Research Scientist for ML Efficiency in Singapore. The ideal candidate will have a PhD in Computer Science, with strong experience in AI research and proven publication records. The role focuses on optimizing generative AI models, developing innovative algorithms, and enhancing deployment pipelines. This position entails collaborating with cross-functional teams to drive new research ideas into production, contributing to cutting-edge technology advancements in the field.

Qualifications

• 4+ years in AI research, either in academia or industry labs.
• Strong publication record in conferences or journals.
• Ability to drive new research ideas through to production.

Responsibilities

• Advance algorithms and optimization techniques for generative AI.
• Innovate improved computation efficiency in deep learning models.
• Enhance model deployment pipeline with new formulations.

Skills

Deep learning

Machine learning

Computational statistics

Technical leadership

Education

PhD in Computer Science or related field

Job description

Staff 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.
• 4 years of experience in a university or industry labs, with Artificial Intelligence (AI) research.
• One or more scientific publication submissions for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).

Preferred qualifications:

• Experience with deep/machine learning, computational statistics, and applied mathematics.
• Knowledge of transformer architecture internals.
• Ability to drive new research ideas from problem abstraction, designing solutions, experimentation, to productionisation in a rapidly shifting landscape.
• Excellent technical leadership and communication skills to conduct multi-team cross-function collaborations.

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.

Google Research Singapore is the very latest addition to the Google Research presence around the globe!

In this role, you will be making significant breakthroughs towards Computational Efficiency of large-scale Generative AI Models (LLMs, Diffusion Models, Generative Videos). 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, 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.