Senior Researcher

Location: Santa Clara, California (primary location only). Relocation support and visa sponsorship available.

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 disciplines like math, neuroscience, physics, and computer science. We look for people who can contribute a strong perspective while collaborating across disciplines. This role is 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. Examples of possible research directions include:

• 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.

Requirements

• 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 role is $133,280 to $190,400 USD, based on skills, qualifications, and experience. This role may also be eligible for a short-term incentive based on company results and individual performance.

Benefits

• Comprehensive health benefits.
• 401K retirement plan.
• Additional benefits to support employee well-being in mind and body.