> Markdown version of [/jobs/ext/2522737-researcher-in-self-improving-machine-learning](https://www.wearedevelopers.com/jobs/ext/2522737-researcher-in-self-improving-machine-learning). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Researcher in Self-Improving Machine Learning - **Company:** Fujitsu America Inc - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Salary:** $133,280.0 - $190,400.0 - **Contract:** Permanent contract - **Skills:** Training Data, Artificial Intelligence, Distributed Computing Environment, Machine Learning, Tensorflow, Pytorch, Deep Learning, Information Technology - **Published:** August 11, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=877f65fd41c34e02 ## About the Role * 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., * 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. ## Description 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., Researchers have substantial freedom to develop new directions based on their interests and the evolving needs of the program. These are some exaples 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. ## Related Videos - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Fireside Chat: Deep Learning, Deep Impact: Harnessing AI for Language Innovation](https://www.wearedevelopers.com/videos/612-fireside-chat-deep-learning-deep-impact-harnessing-ai-for-language-innovation) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [From Model to Metal: An Open Source Stack for Accelerating Intelligence](https://www.wearedevelopers.com/videos/1636-from-model-to-metal-an-open-source-stack-for-accelerating-intelligence) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)