How to apply for Research Intern

About Gensyn

Gensyn is building a protocol to connect AI models and coordinate the compute resources needed for machine intelligence. The company's work sits at the intersection of distributed systems, machine learning, and open, permissionless protocols. This role is for someone who wants to work on the infrastructure layer of AI rather than just training models on centralized hardware.

About the role

As a research intern, you will work on scalable, distributed machine learning systems, focusing on modular architectures, verifiability, continual learning, and scale. You will design and prototype neural network architectures that can operate across decentralized, heterogeneous devices. The work is intended to lead to publications at venues like NeurIPS, ICML, and ICLR.

A typical day

A typical day might involve reading recent papers, prototyping a new neural network architecture, and running experiments on distributed or simulated decentralized hardware. You would also meet with researchers and engineers to discuss progress and plan joint publications. Since the role is remote, clear written communication and self-direction are important.

Who Gensyn is looking for

• Currently enrolled in a PhD program, or in exceptional cases a Master's program, in computer science, machine learning, or a related field.
• Has research experience in deep learning, particularly in areas such as modular neural networks, continual learning, or scalable training.
• Familiar with distributed systems or decentralized compute concepts, and able to reason about verification of neural networks.
• Aims to publish at top-tier AI venues and can work independently on original research in a remote setting.

Tips for this application

• Highlight any research that involves modular architectures, continual learning, or training across heterogeneous or decentralized hardware, since these are the exact focus areas listed.
• Mention specific papers or projects where you contributed to novel neural network architectures or verifiability methods, and note any publication targets or outcomes.
• Explain why you want to work on a protocol for connecting AI models rather than on centralized model training, and show familiarity with Gensyn's approach.
• If you have experience with decentralized compute or blockchain-based systems, connect it directly to the research goals of the internship.
• Include a link to your GitHub or personal research page so the team can see your code and papers.

What to cover in your cover letter

['Your specific research contributions in deep learning, especially in modular architectures, continual learning, or scale.', "Any experience you have with decentralized or distributed training environments, and how it relates to Gensyn's protocol.", 'Your ability to produce original research and target top-tier venues like NeurIPS, ICML, or ICLR.', 'Why the problem of coordinating machine intelligence across open, permissionless networks matters to you.']

Research before applying

• Read Gensyn's website and any public documentation to understand how their protocol connects AI models and compute hardware.
• Look up recent papers or blog posts by Gensyn team members to see their research direction in decentralized machine learning.
• Familiarize yourself with key papers on modular neural networks, continual learning, and verifiable computation in ML.
• Check the NeurIPS, ICML, and ICLR proceedings for recent work on decentralized or distributed training to understand the state of the field.

Likely interview topics

Based on the job description, expect questions about:

• How would you design a neural network architecture that can be trained across heterogeneous, decentralized devices?
• What are the main challenges in verifying neural networks in a decentralized setting?
• Can you discuss a paper you have read on modular or continual learning and how it might apply to Gensyn's work?
• How do you approach scaling deep learning models when compute is not centralized?
• What is your experience with publishing at top-tier AI conferences, and what research direction would you want to pursue at Gensyn?

Common mistakes to avoid

• Applying without any prior research experience in deep learning or distributed systems, as the role requires original research contributions.
• Submitting a generic cover letter that does not mention Gensyn's specific focus on decentralized protocols for AI.
• Failing to show familiarity with the target publication venues or the research areas listed in the responsibilities.