Gensyn is hiring a Research Intern to contribute to scalable distributed machine-learning research, prototype decentralized neural-network architectures, and collaborate on publications.

About the Role

Contribute to cutting-edge research in scalable, distributed machine learning systems alongside experienced researchers and engineers. Explore new ways of building and verifying neural networks that operate across huge, decentralised topologies of heterogenous devices.

Responsibilities

• Contribute to original research in deep learning with a focus on modular architectures, verifiability, continual learning, and scale.
• Design and prototype novel neural network architectures for decentralized compute environments.
• Contribute to joint publications and projects in collaboration with academic and industry researchers targeting top-tier AI venues such as NeurIPS, ICML, and ICLR.

Requirements

• Currently enrolled in a PhD program or, in exceptional cases, a Master’s program in Computer Science, Machine Learning, or a related field.
• Prior experience conducting original research, ideally with authorship or co-authorship on machine-learning papers.
• Strong understanding of deep learning fundamentals and experience with at least one major framework, such as PyTorch, JAX, or TensorFlow.
• Self-directed, curious, and able to thrive in an environment with high autonomy.
• Excellent written and verbal communication skills.

Preferred Qualifications

• Research experience in distributed systems, continual learning, or modular neural architectures.
• A desire to contribute to open research and collaborate with the broader machine-learning research community.
• Experience at the intersection of cryptography and machine learning.

How to Apply

Apply through the official job page.