AI Research Engineer

gradient· Engineering
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🌍 Remote📍 AnywhereFullTime

About this role

Gradient is building the world’s first fully AI runtime—a sovereign, peer-powered infrastructure where intelligence is hosted, served, and owned by the people. The age of Centralized Intelligence is ending. What comes next is open, agentic, and alive at the edge.

We’ve recently completed our $10M seed funding round, led by Pantera Capital and Multicoin Capital, with participation from HSG (formerly Sequoia Capital China) and other distinguished partners. This milestone is further supported by leading angel investors and advisors from spaces across AI, crypto, and beyond.

About the Role

We’re looking for a Research Engineer who’s passionate about shaping the future of AI infrastructure. In this role, you’ll work at the intersection of advanced machine learning models, distributed systems, and on-chain coordination — helping to build a more open, equitable, and resilient intelligence layer for the world.

You’ll join a team of deep technologists exploring how foundation models and intelligent systems can be deployed, trained, and served in environments — while maintaining performance, privacy, and security.

Responsibilities

  • Design and implement protocols for AI training and inference (e.g. federated learning, distributed fine-tuning, secure model serving)

  • Build scalable systems to support AI workloads across heterogeneous networks and devices

  • Contribute to architectural decisions, performance optimization, and reliability engineering

  • Collaborate with researchers and system engineers to translate novel ideas into real-world systems

  • Stay current with the latest advancements in AI, distributed infrastructure, and cryptographic mechanisms

Requirements

  • Strong programming skills in Python, Rust, or Go

  • Experience with AI/ML model training and serving pipelines (e.g. PyTorch, JAX, TensorFlow)

  • Solid foundation in distributed systems, networking, or applied cryptography

  • Familiarity with concepts like federated learning, secure aggregation, or verifiable intelligence

  • Bonus: experience working with blockchain protocols, zkML, or decentralized networks

If you’re ready to challenge the status quo and be part of a transformative journey, we invite you to apply. Together, let’s build a brighter, more inclusive future powered by intelligence.

We’re excited about the path we’re forging — and the talented minds who will help shape it. If you’re passionate about building a community-driven future for AI and eager to make a lasting impact, we’d love to hear from you.

📩 For recruitment-related inquiries only:

✈️ Telegram: @GradientHR

📧 Email: cv@gradient.network

🔗Gradient Official:

Website | X | Discord

Frequently Asked Questions

Is the salary disclosed for the AI Research Engineer position at gradient?
The salary for this AI Research Engineer role at gradient is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Is the AI Research Engineer job at gradient remote?
Yes, this AI Research Engineer position at gradient is remote, with team members based in Anywhere. You can work from home or anywhere in the supported regions.
Is the AI Research Engineer role at gradient full-time or part-time?
This is listed as a FullTime position. It is posted as a AI Research Engineer role in the Engineering department at gradient.
Which team or department does the AI Research Engineer at gradient belong to?
This AI Research Engineer position is part of the Engineering department at gradient. See the full job description for more information about the team structure and responsibilities.
How do I apply for the AI Research Engineer position at gradient?
Click the "Apply Now" button on this page. You will be redirected to gradient's official application portal hosted on ashby where you can submit your application directly.
When was the AI Research Engineer job at gradient posted?
This AI Research Engineer position at gradient was posted on Jun 17, 2025. Apply as soon as possible — early applications are often reviewed first.
AI Research Engineer
gradient
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