Research Intern

You will contribute to original research in deep learning, focusing on modular architectures, verifiability, continual learning, and scale. You will design and prototype novel neural network architectures for decentralized compute environments and collaborate on publications and projects with academic and industry researchers targeting top-tier AI venues such as NeurIPS, ICML, and ICLR.

Responsibilities

• Contribute to original research in deep learning focusing on modular architectures, verifiability, continual learning, and scale
• Design and prototype novel neural network architectures for decentralized compute environments
• Collaborate on publications and joint projects 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, in 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 ML papers
• Strong understanding of deep learning fundamentals
• Experience working with at least one major framework such as PyTorch, JAX, or TensorFlow
• Self-directed and able to thrive in a high autonomy environment
• Excellent written and verbal communication skills
• Research experience in distributed systems, continual learning, or modular neural architectures (preferred)
• Desire to contribute to open research and collaborate with the broader ML research community (preferred)
• Experience at the intersection of cryptography and machine learning (nice to have)

Benefits

• Share of equity and token pool
• Fully remote work
• Visa sponsorship for relocation to the US (available)
• 3-4 all-expenses-paid company retreats per year
• Provision of necessary equipment
• Paid sick leave and flexible vacation
• Company-sponsored health, vision, and dental insurance (United States only)