Senior Research Scientist, ML Foundations

New York, NYOnsiteFull TimeSenior$174,000–$252,000 /yrPosted 1 month agoVisa sponsorship available

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Required skills

Artificial Intelligence
Machine Learning
Python
TensorFlow
Jax
publications
ML conferences

Nice to have

research agendas
reinforcement learning
deep learning
distributed training
ML solutions
real world problems

Role summary

Google Research is seeking a Senior Research Scientist specializing in ML Foundations. This role involves conducting fundamental research in machine learning, developing algorithm prototypes, and evaluating them. The scientist will publish findings in top ML venues and contribute to product improvements by partnering with Waymo and other Product Areas. Responsibilities include setting up large-scale tests, deploying ideas, and collaborating with internal and external research communities. The position requires a PhD or equivalent experience, with a focus on ML algorithm implementation in Python and deep learning frameworks.

Minimum qualifications:

PhD in Computer Science, Artificial Intelligence, Machine Learning, a related field, or equivalent practical experience.
2 years of experience with research in machine learning or a related field, with publications at ML conferences (e.g., ICML, NeurIPS, ICLR)
Experience with ML algorithm and model implementation in Python.
Experience with deep learning frameworks (TensorFlow, Jax or others).

Preferred qualifications:

1 year of experience owning and initiating research agendas.
Experience with reinforcement learning research and applications.
Experience in deep learning and distributed training.
Track record of developing ML solutions for real world problems.

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'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 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.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities:

Conduct research in Machine learning, e.g., derive theoretical insights, develop alogrithm prototypes and evaluate them on academic and internal benchmarks.
Communicate research findings with the external community through publications at top ML venues and internal stakeholders through tech reports and presentations.
Develop approaches for more robust simulator learning and productionize them to improve driving simulation models for Waymo.
Partner with Waymo, and other Product Areas, to turn insights from algorithmic research and proof-of-concept implementations into product improvements.

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