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Gradient Tech Stack

Distributed AI infrastructure for inference and reinforcement learning

Technology, Information and Internet Singapore 11–50 employees Founded 2024 Privately Held
gradient.network LinkedIn

Gradient is an AI infrastructure lab building three interconnected systems: Parallax (distributed inference across heterogeneous hardware), Echo (asynchronous reinforcement learning framework), and Lattica (peer-to-peer networking layer). The stack reveals hardware-agnostic design—PyTorch, JAX, TensorFlow alongside Rust and Go—optimized for deploying AI across mixed device pools rather than centralized data centers. Early traction on Lattica (millions of peers) and Echo-2's 90%+ cost reduction in post-training suggest the team is past conceptual stage.

Tech Stack 10 technologies

Core StackPython Rust Go PyTorch TensorFlow Java C++ JAX
AdoptingReact Next.js

What Gradient Is Building

◆Challenges

  • Accelerating adoption of next-generation intelligence systems

▲Active Projects

  • Distributed inference system
  • Trustless collaboration platform
  • Incentive mechanism design
  • Ai training and inference protocols
  • Scalable ai workload systems
  • Frontend development
  • Backend engineering
  • Ai infrastructure
  • Design systems for scalable bd efforts
  • Structure partnerships for product direction and community growth

Hiring Activity

Minimal5 roles · 0 in 30d

Department

Engineering
2
Sales
2
Research
1

Seniority

Mid
2
Intern
1
Junior
1
Lead
1
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About Gradient

Gradient operates as an AI research lab focused on decentralized AI infrastructure. The company's three core products address specific bottlenecks: Parallax handles automatic model sharding and request routing across GPUs and consumer hardware; Echo decouples RL training from rollout collection to reduce post-training compute; Lattica provides global peer-to-peer coordination. Founded in 2024 and backed by Pantera Capital, Multicoin Capital, and HSG, the company is currently hiring research and engineering talent from Singapore. Active projects span distributed inference systems, incentive mechanism design, and partnership development around the open infrastructure thesis.

HeadquartersSingapore
Company Size11–50 employees
Founded2024
Hiring MarketsSingapore

Frequently Asked Questions

What is Gradient's main technology stack?

Core languages: Python, Rust, Go. ML frameworks: PyTorch, JAX, TensorFlow. The mix reflects hardware-agnostic, distributed-systems thinking required for inference across heterogeneous devices.

What does Parallax do?

Parallax is a distributed inference engine that automatically shards models and routes requests across mixed hardware (NVIDIA GPUs, Apple Silicon, other devices), enabling local, offline AI deployment.

What results has Echo achieved?

Echo-2, Gradient's distributed RL framework, reduced post-training costs for a 30B parameter model by over 90% (from ~$4,490 to ~$425) by decoupling rollouts from training asynchronously.

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