Research Scientist, Algo Spark

Google
Mountain View, CA, USA

About the job

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. Our team focuses on various aspects of algorithmic improvements in privacy, security, model architectures, Artificial Intelligence reasoning, and knowledge. In this role, you will develop new algorithms covering various topics including privacy and Machine Learning. You will push for new directions in Artificial Intelligence for mathematics and theoretical research. You will take insights from research into Google products across different Product Areas.

Responsibilities

Design and develop algorithms.

Push new directions in artificial intelligence (AI) for mathematics and theoretical research.

Take insights into Google products.

Publish high-quality research at conferences (e.g., NeurIPS, ICML, ICLR, StOC, FOCS) to maintain Google's leadership in the global scientific community.

Qualifications

Minimum

PhD degree in Computer Science, a related field, or equivalent practical experience.

Experience with Machine Learning Algorithms.

One of more scientific publication submission(s) for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).

Preferred

Knowledge of linear programming with excellent coding skills in Python.

Understanding of machine learning algorithms and research.