The role involves driving go-to-market execution and building operational infrastructure to support growth. The associate will also handle strategic projects and provide direct operational support to the founder and Chief of Staff.
Pluralis Research
7 Remote Job Openings at Pluralis Research
Machine Learning Engineer - ML Training Platform
Pluralis Research
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Full Time
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2 months ago
Pluralis Research
The role involves designing resource management systems for multi-cloud infrastructure and architecting fault-tolerant infrastructure for distributed machine learning. Additionally, the engineer will build systems that simulate real-world network conditions to ensure efficient data flow across consumer nodes.
Machine Learning Engineer - Distributed ML Systems
Pluralis Research
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Full Time
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2 months ago
Pluralis Research
Design and implement large-scale distributed training systems optimized for low-bandwidth, high-latency conditions. Build resilient training systems that can handle node failures and dynamic participant changes.
Machine Learning Engineer - ML Training Platform
Pluralis Research
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3 months ago
Pluralis Research
The role involves designing and implementing large-scale distributed training systems optimized for low-bandwidth, high-latency conditions, focusing on model parallelism and communication overhead reduction. Responsibilities also include architecting resilient training systems capable of handling node failures and designing decentralized coordination peer-to-peer topologies.
The core responsibility is solving hard research problems within Protocol Learning and publishing foundational papers in Tier-1 Venues. This involves advancing the state-of-the-art in decentralized training of large models.
The core responsibility is to solve foundational research problems related to Protocol Learning and publish findings in tier-1 venues. This involves significant research excellence and contributions to the field.
Contribute to groundbreaking research in Protocol Learning during your PhD. Conduct novel research with the explicit goal of publishing in tier-1 ML conferences.
