Staff Research Scientist, ML Efficiency, Google Research - Singapore

GOOGLE ASIA PACIFIC PTE. LTD.; Singapore; On-site; SGD 100,000 - 130,000; Full time

Job summary

A global technology company in Singapore is seeking a Research Scientist to work on advanced algorithms for generative AI models. This role entails innovating architectures, improving deployment pipelines, and collaborating across teams to optimize efficiency. Candidates should possess a PhD in Computer Science, 7 years of AI research experience, and have published in scientific conferences. The position is critical for enhancing computational efficiency in AI models, aiming to benefit millions worldwide.

Qualifications

• PhD degree in Computer Science, a related field, or equivalent practical experience.
• 7 years of experience in AI research.
• One or more scientific publication submissions.

Responsibilities

• Advance algorithms for efficiency in generative AI models.
• Innovate architectures that improve computation efficiency.
• Improve model deployment pipeline.
• Collaborate with hardware and software teams for optimization.
• Optimize latency and bandwidth workloads.

Skills

Machine Learning

Deep Learning

Data Mining

Algorithm Development

Technical Leadership

Education

PhD in Computer Science or related field

Job description

Product area

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.

Job description

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 set up 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'll 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.

Additional job description

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).

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.

Job 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.

Minimum qualifications

• PhD degree in Computer Science, a related field, or equivalent practical experience.
• 7 years of experience in a university or industry labs, with primary emphasis on AI research.
• One or more scientific publication submissions for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).

Preferred qualifications

• Understanding 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.
• Passionate for deep/machine learning, computational statistics, and applied mathematics.