AI Researcher
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Before you apply
LocationAnywhere
Work moderemote
Typefull-time
DepartmentResearch
Company size4+ people
PostedJun 26, 2025 · 1y ago
Verified live2d ago
At a glanceSummarised by Seekless from the posting.
Background in computer science, machine learning, applied mathematics, or a related field
Demonstrated research experience in distributed ML, secure computation, federated learning, or incentive systems
Ability to write clear technical documentation and communicate complex ideas effectively
Experience with protocols, zero-knowledge proof systems, or system-level AI optimization
Skills
machine learning
distributed ML
secure computation
federated learning
protocols
zero-knowledge proof systems
system-level AI optimization
About the company
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
Gradient Network is looking for a Researcher with a strong foundation in machine learning, systems, or cryptography to help reimagine how intelligence is created and shared in world.
You’ll investigate the core scientific challenges of AI — such as distributed training, model integrity, incentive design, and privacy-preserving intelligence — and work alongside engineers to bring these breakthroughs into production.
This role is ideal for someone who thrives in ambiguity, prototypes fast, and wants their work to shape the trajectory of next-gen AI infrastructure.
Responsibilities
• Conduct original research on learning, distributed inference, and trustless collaboration in AI systems
• Contribute to the design of incentive mechanisms that support open and community-driven AI networks
• Prototype experimental systems and communicate findings internally and externally
• Translate theoretical insights into practical designs with engineering collaborators
• Engage with the global research community in AI, ML systems, and applied cryptography
Requirements
• Background in computer science, machine learning, applied mathematics, or a related field
• Demonstrated research experience in distributed ML, secure computation, federated learning, or incentive systems
• Ability to write clear technical documentation and communicate complex ideas effectively
• Bonus: experience with protocols, zero-knowledge proof systems, or system-level AI optimization
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: [email protected]
🔗Gradient Official:
Website | X | Discord
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