Research Engineer - Decentralized AI Systems

Benefits

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Work mode

Remote From the posting source checked Jun 20, 2026

In-office days

0 days From the posting source checked Jun 20, 2026

Schedule

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Weekend work

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Company

Company stage

Early From the posting source checked Jun 20, 2026

Application

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Deadline

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State eligibility is not yet verified.

About this role

Research Engineer - Decentralized AI Systems United States | Remote | Canada | Argentina | Brazil | Mexico Location: Remote (Global) Type: Full-time Company: Yotta Labs Apply: [email protected] 🧠 About Yotta Labs Yotta Labs is pioneering the development of a Decentralized Operating System (DeOS) for AI workload orchestration at a planetary scale. Our mission is to democratize access to AI resources by aggregating geo-distributed GPUs, enabling high-performance computing for AI training and inference on a wide spectrum of hardware-from commodity to high-end GPUs. Our platform supports major large language models (LLMs) and offers customizable solutions for new models, facilitating elastic and efficient AI development. 🛠️ Role Overview We are seeking a Research Engineer with a passion for decentralized systems and AI infrastructure. In this role, you will contribute to the development of our DeOS framework, focusing on optimizing AI workloads across a heterogeneous network of GPUs. Your work will directly impact the scalability and performance of AI applications deployed on our platform. 🎯 Responsibilities - Design and implement components of the DeOS for efficient AI workload orchestration. - Develop and optimize software for managing geo-distributed, heterogeneous GPU resources. - Collaborate with cross-functional teams to integrate support for various LLMs and AI models. - Ensure high availability and fault tolerance in decentralized computing environments. - Contribute to open-source projects and engage with the developer community. ✅ Qualifications - Proficiency in AI programming languages such as Python - Experience with distributed systems, cloud computing, or blockchain technologies. - Familiarity with AI frameworks

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