Research Scientist at Fujitsu's Self-Improving ML team (Sunnyvale, CA)
The Self-Improving ML team at Fujitsu aims to create algorithms that automatically improve themselves, enabling them to handle a wider range of tasks with improved accuracy while requiring less training data.
About Fujitsu
Fujitsu’s mission is to make the world more sustainable by building trust in society through innovation. Fujitsu is the largest IT company in Japan and among the largest in the world. Join us in shaping the future of the world.
https://www.fujitsu.com/global/about/purpose/
About the role
We are seeking creative researchers to join the Self-Improving ML team at our office in Silicon Valley. This is an opportunity to pioneer and prototype general-purpose AI algorithms for vision and text that possess the capability to enhance themselves autonomously. This position is suited for those who enjoy exploring profound questions in ML research, excel in roles that encourage ambitious open-ended objectives, and are highly motivated to make valuable contributions towards deploying general AI systems for a sustainable world.
Only candidates with a PhD (or close to completion) will be considered.
Job Responsibilities
Research and prototype ML algorithms that automatically improve themselves to tackle a wider range of vision and text tasks. Demonstrate algorithmic improvements in increasingly more challenging vision and text tasks using a lower amount of data. Write high quality, scalable python code. Design and conduct experiments to explore and validate novel AI methodologies. Publish research papers in scientific journals and conferences. Showcase the work via presentations in talks, conferences, and workshops. Develop tools and strategies to deploy the research to projects for building a sustainable world. Apply the ML research projects to real world applications for building a sustainable world.Essential requirements
We aim to keep growing our team’s expertise across a broad spectrum, from creating and analyzing experiments to designing and implementing cutting-edge architectures at scale and deploy them at scale. To achieve this, we have the following requirements:
• Only candidates with a PhD (or close to completion) in machine learning, computer science, neuroscience, mathematics, statistics, physics, or related fields will be considered.
• Track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as publications or projects.
• Possess the ability to own and pursue a research agenda and carry out long-running projects.
• Experience with one or more deep learning libraries (PyTorch, TensorFlow, Jax)
• Ability to collaborate effectively with multiple researchers in a large-scale research project and partner with the deployment team. It is essential to feel comfortable in a collaborative environment. Preferred requirements
• Experience in interdisciplinary research collaborations.
• Have experience in research mentorship.
• Experience in creating high-performance implementations of deep learning algorithms.
About the team
Our research focuses on the next frontier: developing self-improving machine learning systems that leverage AI to optimize and enhance AI itself. Our core thesis is that by enabling AI systems to autonomously refine their own architecture, learning algorithms, and data utilization, we can achieve orders of magnitude improvement over current methodologies.
An AI system is built upon three fundamental layers: the infraestructure layer, encompassing both hardware and software infrastructure; the modeling layer, which defines model architectures and training methodologies; and the data layer, where data selection and supervision strategies come into play. Traditionally, each of these layers relies heavily on human intervention, demanding specialized expertise and manual tuning. Yet, self-improving ML systems will be able to optimize these elements with unparalleled precision and efficiency, surpassing the capabilities of human experts.
By pioneering self-improving ML, we aim to make AI not just a powerful tool for automatically solving today’s challenges but a dynamic entity that can evolve independently to tackle the complex problems of tomorrow. This evolution goes beyond technological advancement; we believe it can drive meaningful change. Our research is contributing to more sustainable use of resources, reduce energy consumption, and ultimately enable AI to address environmental and societal challenges more effectively. Through this work, we aspire to harness AI’s potential to make the world not only smarter but also more sustainable for future generations.
Fujitsu salaries are aligned to the specific geographic location in which the work is primarily performed. It is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the circumstances of each situation. The pay range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to: specific skills, qualifications, experience, and comparison to other employees already in this role. The pay range for this position is estimated at $122,774.40 to $175,392.00 USD. Additionally, this role may be eligible for a short-term incentive based on company results and individual performance.
As a technology company, Fujitsu recognizes that human resources are its most important capital. To create an environment where all employees can work positively and healthily, both in mind and body, we offer a full range of health, 401K, and other benefits.
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