Junior LLM Developer
Large Language Model Development for Blockchain
Confirmed live in the last 24 hours
Openmesh Networks

11-50 employees

Decentralized Web3 data storage network
Company Overview
Openmesh Network distinguishes itself by developing a decentralized data infrastructure that prioritizes the democratization of information access and challenges the centralized control of data by a few large corporations. By offering a platform that is decentralized, distributed, and immutable, Openmesh facilitates universal access to Web3 data, ensuring that users can connect, store, and process information freely and without gatekeepers. This approach not only aligns with the principles of a free and democratic society but also positions Openmesh as a key player in the evolution of the internet's infrastructure over the coming decades.

Company Stage

N/A

Total Funding

N/A

Founded

2020

Headquarters

Sydney, Australia

Growth & Insights
Headcount

6 month growth

4%

1 year growth

4%

2 year growth

4%
Locations
New York, NY, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
Natural Language Processing (NLP)
Data Analysis
CategoriesNew
AI & Machine Learning
Applied Machine Learning
Natural Language Processing (NLP)
Requirements
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.
  • Experience with large language model frameworks (e.g., GPT, BERT).
  • Strong programming skills in languages such as Python.
  • Understanding of blockchain and decentralized technologies.
  • Ability to work in a collaborative and research-oriented environment.
Responsibilities
  • LLM Development: Contribute to the development of large language models (LLMs) tailored for applications within the blockchain ecosystem.
  • NLP Integration: Integrate natural language processing (NLP) capabilities into blockchain applications to enhance user interactions and data processing.
  • Model Training: Participate in the training and fine-tuning of LLMs for specific use cases within the Xnode and Pythia ecosystems.
  • Collaboration: Collaborate with developers, data scientists, and product teams to implement LLMs effectively.
  • Continuous Learning: Stay abreast of advancements in LLM technology and blockchain applications to inform development strategies.