AI Research Scientist - Generative AI and Multi-Party Computation (MPC)

Nillion is a web3 infrastructure project based on a novel cryptographic innovation called Nil Message Compute (see presentation at Cambridge University). The new technology enables Information-Theoretic Secure decentralized data storage and computation.

As reported by TechCrunch, Nillion raised $25 million at a $180 million valuation in the midst of the bear market of 2022 - the highest valuation for a Seed Round reported in Q4-2022. The project has attracted some of the top talent in tech, including the Founding Engineer of Uber (Conrad Whelan), Founder of Indiegogo (Slava Rubin), Associate General Counsel of Coinbase (Lindsay Danas Cohen), Co-Founder of Hedera Hashgraph (Andrew Masanto) and several other high profile team members. The project has also won several industry awards, including the CoinList Seed Program (see CoinList Tweet here) and Polygon Co-Founder’s Web3 Accelerator Program, Beacon.

Nillion is bringing to life fast, permissionless, decentralized secure storage and private computation that fundamentally improves the way that data is processed, analyzed and shared. The protocol is looking for a generative AI expert to join the team in researching use cases within that field. We are a remote-first organization looking to build an engineering team primarily focused on European and US East Coast time zones. 

We are seeking an experienced AI Research Scientist with a strong background in generative AI models and an interest in Privacy Enhancing Technologies (PET). The ideal candidate will explore the intersection of generative AI and MPC, developing new techniques and methodologies that allow for secure, distributed AI computations. You will be working with the Nillion Product team and report to Nillion’s AI Product Lead.

Requirements

• Conduct cutting-edge research on AI models within the framework of MPC.
• Collaborate with a multidisciplinary team to integrate MPC techniques into generative AI systems.
• Publish research findings in top-tier journals and conferences.
• Stay abreast of the latest developments in AI and MPC fields.
• Prototype and simulate MPC-based generative models to evaluate their performance and feasibility

Qualifications:

• PhD in Computer Science, Machine Learning, Mathematics, or a related field.
• Proven track record of research in generative AI models, demonstrated through publications, patents, or software contributions.
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch).
• Proficiency in programming languages such as Python, C++, or Rust.
• Excellent problem-solving and analytical skills.
• Strong written and verbal communication skills.

Preferred Skills:

• Post-doctoral or industry experience in a related field.
• Experience with federated learning, differential privacy, or other privacy-preserving technologies.
• Strong mathematical foundation in cryptography, specifically in MPC.
• Contributions to open-source projects in the AI or privacy tech space.

Benefits

• Competitive salary and benefits package.
• Flexible working hours and remote work opportunities.
• A dynamic and supportive research environment.
• Access to state-of-the-art computational resources.
• Opportunities for continued learning and professional development.
• Collaboration with leading academics and industry experts.