Senior Researcher

About the Role

We are seeking creative and intellectually ambitious researchers to join our multidisciplinary Self-Improving ML team in Silicon Valley. Our goal is to develop AI systems that can improve how AI itself is built. We study fundamental questions at the intersection of learning, generalization, data, and automated discovery:

• What determines whether a model generalizes beyond its training data?
• How can an AI system identify or generate the data it needs to improve?
• Can we automate the creation of new models, learning algorithms, and research ideas?

Our team brings together researchers from different disciplines like math, neuroscience, physics and computer science. Rather than expecting everyone to fit the same profile, we look for people who can contribute a strong perspective while collaborating across disciplines. This role is particularly suited to researchers who enjoy pursuing deep, open-ended questions, building and testing unconventional ideas, and translating fundamental research into working AI systems.

Responsibilities

Researchers have substantial freedom to develop new directions based on their interests and the evolving needs of the program. These are some examples of possible research directions:

• Develop and prototype algorithms that enable AI systems to improve their models, learning strategies, data, or problem-solving processes.
• Investigate the relationship between training data and generalization, including methods for automatically selecting, generating, or refining data.
• Explore approaches for automating elements of creativity, scientific discovery, and ML research.
• Design rigorous experiments to evaluate novel hypotheses and understand why methods succeed or fail.

Essential Qualifications

• PhD, or near completion of a PhD, in machine learning, computer science, neuroscience, mathematics, statistics, physics, or a related field.
• A demonstrated ability to develop original ideas or substantially improve existing methods, as shown through research publications, projects, or comparable accomplishments.
• Strong interest in fundamental questions involving learning, generalization, data, automated discovery, or self-improving systems.
• Ability to independently formulate and pursue a research direction and carry a long-term project from hypothesis to experimental validation.
• Experience with at least one deep-learning framework, such as PyTorch or TensorFlow.
• Strong collaboration skills and enthusiasm for working with researchers from different technical backgrounds.
• Ability to communicate research ideas clearly and translate them into well-designed experiments and reliable implementations.

Preferred Qualifications

• Experience conducting interdisciplinary research.
• Expertise that complements conventional ML research, such as neuroscience, mathematics, statistics, physics, optimization, or automated scientific discovery.
• Experience developing high-performance implementations of deep-learning algorithms.
• Experience with large-scale experimentation or distributed training and inference.
• Experience mentoring researchers, students, or engineers.

Pay

The pay range for this position is estimated at $133,280 to $190,400 USD. Additionally, this role may be eligible for a short-term incentive based on company results and individual performance.

Benefits

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.

Schedule

Primary Location Only (Santa Clara, California). Relocation supported and visa sponsorship approved for this role.