AI Systems Architect

2 weeks ago

Austin, Texas, United States Eidon AI Full time
Location: Bay Area candidates are also welcome
About Eidon AI

At Eidon AI, we are a collective of AI and blockchain innovators, comprised of experts from leading tech firms and investment institutions. Our mission is to collaboratively build a fully decentralized AI infrastructure that operates in a trustless and permissionless manner, ensuring equitable rewards for all contributors and enhancing the welfare of humanity. Our initial focus is on decentralizing AI Data Availability and Data Restaking by linking data providers with consumers in a decentralized marketplace.

Our team is compact, functioning within a flat organizational structure, and is driven by a commitment to engineering excellence. Eidon is an ideal environment for individuals who thrive on ownership, possess a strong sense of curiosity, and are eager to tackle challenges across various domains. All technical staff share the designation of "Member of the Technical Guild."

We expect all employees to be proactive and contribute directly to our goal of advancing decentralized AI. Leadership opportunities are awarded to those who demonstrate initiative and consistently achieve outstanding results. A strong work ethic and effective prioritization skills are essential. We prioritize productivity over lengthy meetings and presentations.

Effective communication and active listening are crucial for all engineers and researchers. Team members are encouraged to share knowledge openly, concisely, and respectfully.

At Eidon AI, we do not employ recruiters, project managers, or administrative personnel. Each application is evaluated directly by a technical team member.

We are backed by top-tier venture capitalists from Silicon Valley.
Job Overview

As an AI Engineer at Eidon AI, you will be at the forefront of pushing the limits of AI within decentralized frameworks. Your role will involve developing AI agents, researching novel decentralized AI models and architectures that utilize our distinctive data ecosystem, and driving progress in AI research and applications while ensuring fairness and accessibility for all stakeholders.
Key Responsibilities
  • Design, develop, and implement AI models and algorithms in a decentralized data environment.
  • Collaborate with Data Engineers to optimize data processing and model training workflows.
  • Investigate and apply cutting-edge AI methodologies to address complex challenges in data availability and distribution.
  • Create AI Agents for data manipulation and advanced RAG systems.
  • Engage with the community to share insights, models, and advancements, promoting an open and collaborative decentralized AI research environment.
Qualifications
  • Background in Engineering or Science (e.g., Computer Science, Computer Engineering, or Electrical Engineering degree or equivalent experience).
  • Strong expertise in machine learning, deep learning, and AI model development.
  • Proficiency with machine learning frameworks (e.g., TensorFlow, PyTorch, JAX) and programming languages such as Python.
  • Experience in training large neural networks at scale and fine-tuning various specialized models.
  • Ability to create AI Agents.
  • Experience in developing high-performance RAG systems and adapting them to distributed environments.
  • Familiarity with all data modalities: text, audio, images, video, real-time, and real-world data.
  • Skills in profiling, debugging, and optimizing GPU utilization across multiple hosts.
  • Capability to rapidly implement the latest state-of-the-art methods from deep learning literature.
  • Innovative mindset for developing new algorithms and methods that advance decentralized AI systems.
  • Experience in building distributed training systems for AI models.
  • Proficiency in configuring and troubleshooting hardware and operating systems for optimal performance.
  • Experience working with JAX/XLA for multi-host training.
  • Ability to write custom CUDA kernels in C++ or via Triton.
  • Experience in debugging and customizing third-party source code.
  • Knowledge of blockchain and decentralized technologies applicable to decentralized AI.

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