
Organizing the world's information and making it universally accessible.
Staff Research Scientist, ML Efficiency, Google Research
-
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.
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'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.
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.
Google will be prioritizing applicants who have a current right to work in Singapore, and do not require Google's sponsorship of a visa.
-
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 of more scientific publication submissions for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).
Total Views
0
Total Apply Clicks
0
Total Mock Apply
0
Total Bookmarks
0
Similar jobs

Principal AI/ML Engineer
Abbott · United States > Santa Clara : Building B - SC

Staff Product Engineer, AI
Intercom · Berlin, Germany

Principal Forward Deployed AI Engineer
Turing · San Francisco, California, United States

Senior Consultant - Tech Consulting - National - CNS - TC - AI AND DATA - New Delhi
EY

Senior Staff Machine Learning Engineer - Ads Prediction, Signals & Quality
Apple · Cupertino, CA
About Google

Google specializes in internet-related services and products, including search, advertising, and software.
10,001+
Employees
Mountain View
Headquarters
$1,700B
Valuation
Reviews
10 reviews
4.5
10 reviews
Work-life balance
3.2
Compensation
4.3
Culture
4.1
Career
4.2
Management
3.8
82%
Recommend to a friend
Pros
Great benefits and perks
Innovative and interesting work
Career development and learning opportunities
Cons
High pressure and expectations
Long hours and heavy workload
Fast-paced and overwhelming environment
Salary Ranges
57,503 data points
Junior/L3
L6
L7
L8
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
L3
L4
L5
Junior/L3 · Data Scientist L3
0 reports
$176,704
total per year
Base
-
Stock
-
Bonus
-
$150,298
$203,110
Interview experience
9 interviews
Difficulty
3.4
/ 5
Duration
14-28 weeks
Offer rate
44%
Experience
Positive 0%
Neutral 56%
Negative 44%
Interview process
1
Application Review
2
Online Assessment/Technical Screen
3
Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
Common questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Product Sense
Latest updates
Our eighth generation TPUs: two chips for the agentic era - blog.google
blog.google
News
·
1w ago
Google Maps on Android Auto now shows bigger labels on streets along your route [Gallery] - 9to5Google
9to5Google
News
·
1w ago
Google to invest up to $40 billion in AI rival Anthropic - Reuters
Reuters
News
·
1w ago
Google to invest up to $40B in Anthropic in cash and compute - TechCrunch
TechCrunch
News
·
1w ago