Job – Blockchain Senior Software Engineer/Technical Lead


  • Collaborating with CTO/PM/BD to design FedML Blockchain Layer 1 and Layer 2 Infrastructure to support on-chain AI and AI marketplace
  • Research and development on tokenomics for the data and AI community
  • Lead a blockchain engineering team
  • Working with the open-source community by collaborating with external contributors on our codebase


  • Advanced proficiency in programming languages, such as Go, Rust, C++, Java, and Python.
  • Extensive experience in common algorithms, data structures, and their computation, communication, and memory complexities; prior experiences in performance optimization preferred
  • Experience in blockchain infrastructure development, proficiency with Smart Contract (e.g., Solidity), the Ethereum Virtual Machine (EVM), consensus algorithm, wallet interfaces, and RPCs, with production-level deployments of non-trivial protocols and related security audits
  • Experience in cryptography, especially in zero-knowledge proof
  • Strong ability to develop and debug in distributed systems, P2P networks, etc.
  • A good understanding of machine learning and AI is preferred but not required
  • Passion for working with startups and fast-paced, ambitious environments is a plus
  • Good communication and writing skills in an English environment.

About the job

FedML, Inc. ( aims to provide an end-to-end machine learning operating system for people or organizations to transform their data to intelligence with minimum efforts. FedML stands for “Fundamental Ecosystem Development/Design for Machine Learning” in a broad scope, and “Federated Machine Learning” in a narrow scope. At the current stage, FedML is developing and maintaining a machine learning platform that enables zero-code, lightweight, cross-platform, and provably secure federated learning and analytics. It enables machine learning from decentralized data at various users/silos/edge nodes, without the need to centralize any data to the cloud, hence providing maximum privacy and efficiency. It consists of a lightweight and cross-platform Edge AI SDK that is deployable over edge GPUs, smartphones, and IoT devices. Furthermore, it also provides a user-friendly MLOps platform to simplify decentralized machine learning and real-world deployment. FedML supports vertical solutions across a broad range of industries (healthcare, finance, insurance, smart cities, IoT, etc.) and applications (computer vision, natural language processing, data mining, and time-series forecasting). Its core technology is backed by more than 3 years of cutting-edge research of its co-founders, who are recognized leaders in the federated machine learning community. Recently, FedML has raised around 2 million USD to scale up the product and engineering team.

FedML’s researchers and software engineers develop the next-generation platform for machine learning and artificial intelligence. We’re looking for researchers or engineers who bring fresh ideas from all areas, including machine learning and its applications in compute vision, natural language processing, data mining, as well as large-scale system design and implementation for distributed/cloud computing/systems, security/privacy, mobile/IoT systems, networking, Web UI design and development. As a software engineer, you will work on a specific project critical to our customers’ needs. We hope our engineers to be a faster learner and be enthusiastic to tackle new problems as we continue to push technology forward. You will design, develop, test, deploy, maintain, and enhance software solutions.


CEO – Salman Avestimehr 

Salman Avestimehr is a world-renowned expert in federated learning with more than 20 years of R&D leadership in both academia and industry. He has been a Dean’s Professor and the inaugural director of the USC-Amazon Center on Trustworthy Machine Learning at University of Southern California. He has also been an Amazon Scholar in Amazon. He is a United States Presidential award winner for his profound contributions in information technology, and a Fellow of IEEE.

CTO – Chaoyang He 

Chaoyang He is PhD from the CS department at the University of Southern California, Los Angeles, USA. He has research experience on distributed/federated machine learning algorithms, systems, and applications, and published papers at top-tier conferences such as ICML, NeurIPS, CVPR, ICLR, AAAI, and MLSys. He also has rich experience in industry in the areas of distributed/cloud computing and mobile/IoT systems. He was an R&D Team Manager and Principal Software Engineer at Tencent, and also worked as researcher/engineer at Google, Facebook, Amazon, Baidu, and Huawei. He has received a number of awards in academia and industry. Homepage


We prefer California, but we also support office in other states or work from home if necessary.