Research Intern, FedML

Federated, Distributed Machine Learning, Systems

Salary not provided

JavaScript

Python

Java

Tensorflow

PyTorch

San Francisco Bay Area

Office located in Sunnyvale, CA

Open-source AI & Web3 community

Job no longer available

Open-source AI & Web3 community

1-20 employees

B2BArtificial IntelligenceMarketplaceMachine LearningSaaSData AnalysisWeb 3.0

Job no longer available

Salary not provided

JavaScript

Python

Java

Tensorflow

PyTorch

San Francisco Bay Area

Office located in Sunnyvale, CA

1-20 employees

B2BArtificial IntelligenceMarketplaceMachine LearningSaaSData AnalysisWeb 3.0

Company mission

To create an ecosystem that will meet enterprise demands for custom AI models.

Job

Company

Role

Who you are

Bachelor’s degree or equivalent practical experience in computer science or related areas
2 years of experience with software development in one or more programming languages (Python, Java, JavaScript, C/C++) or 1 year of experience with an advanced degree
2 years of experience with data structures or algorithms in either an academic or industry setting

Desirable

Good communication and writing skills in English environment
Good research skills in machine learning or distributed/federated machine learning; familiar with PyTorch or TensorFlow
Developing new algorithms or system-algorithm co-design for federated or distributed training platform
Solve research challenges such as statistical or system heterogeneity, security, privacy for federated learning or distributed training platform
Have at least one related paper published at top-tier machine learning or system conferences

What the job involves

Participate in the development of machine learning platform and open source communities
Responsible for the foundational research and product development, and continuously improve the R&D efficiency
Responsible for feature development, algorithm optimization of the platform, improving user experience and usability through cutting-edge or mature technologies
Participate in or lead design reviews with peers and stakeholders to decide amongst available technologies
Review code developed by other developers and provide feedback to ensure best practices
Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback

Our take

FedML was founded to address the concerns about the unrestrained data-sharing capacities of machine learning models and how society is becoming increasingly reliant on them. Using a zero-code approach to federated learning (a way to train AI models without anyone seeing or touching your data), FedML defends against the ever-growing potential of centralized data breaches. This empowers enterprises to find solutions that leverage datasets whilst keeping personal details confidential.

Founded by scholars and researchers at the University of Southern California, the company is, at its core, an open-source community and enterprise platform focused on developing machine learning and artificial intelligence. FedML has amassed more than 3000 community members and 2000 enterprise industry users who leverage its tools to simplify decentralized data across industries such as healthcare, IoT, and fintech.

FedML has been successful in receiving two rounds of seed funding since founding in 2022. The most recent funding will be used to expand development and adoption for its distributed MLOps platform.

Freddie

Company Specialist at Welcome to the Jungle

Company

Funding (2 rounds)

Jul 2023

$11.5m

SEED

Mar 2022

$2m

SEED

Total funding: $13.5m

Company HQ

Sunnyvale, CA

Leadership

Salman Avestimehr

(CEO)

Current Dean’s Professor of Electrical and Computer Engineering & Computer Science at the University of California. Previous "Amazon Scholar" at Amazon and Associate Professor at Cornell University.

Chaoyang He

(CTO)

Current Research Assistant for Google, Amazon and Facebook. Previous Doctoral Researcher at the University of Southern California and Engineering Manager at Tencent.

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