Senior/Staff Machine Learning Engineer - Distributed Systems

torentify • United States

Remote Visa Sponsorship

This Job is No Longer Active This position is no longer accepting applications

AI Summary

Design and implement large-scale distributed machine learning training infrastructure for decentralized, community-owned models. Optimize model parallelism, GPU utilization, and peer-to-peer networking for heterogeneous, low-bandwidth environments. Requires 5+ years of experience in distributed systems, Python, and large-scale ML frameworks like FSDP or DeepSpeed.

Key Highlights

Build novel infrastructure for distributed ML training across consumer-grade internet connections.

Optimize for heterogeneous hardware, low-bandwidth, and high-latency environments.

Develop resilient peer-to-peer communication and fault-tolerant training systems.

Searching for Machine Learning & AI roles that provide visa sponsorship? Connect with international employers through Machine Learning & AI Jobs with Visa Sponsorship opportunities actively seeking talented professionals.

Key Responsibilities

Design and implement large-scale distributed machine learning training systems.

Optimize distributed training for heterogeneous hardware operating in low-bandwidth and high-latency environments.

Develop model-parallel training strategies, including data, tensor, and pipeline parallelism.

Implement custom sharding techniques to reduce communication overhead.

Optimize GPU utilization, memory efficiency, and overall compute performance.

Develop reliable checkpointing and state synchronization mechanisms.

Build recovery systems for long-running and fault-prone training workloads.

Develop monitoring and metrics systems to track training progress, model quality, and infrastructure bottlenecks.

Architect resilient distributed training systems capable of handling node failures and network partitions.

Design systems that support participants dynamically joining or leaving the network.

Develop peer-to-peer communication and coordination mechanisms.

Implement peer discovery, NAT traversal, dynamic routing, and connection lifecycle management.

Analyze and optimize communication patterns across distributed nodes.

Reduce network latency and bandwidth requirements in multi-participant training environments.

Build systems capable of operating reliably across non-co-located infrastructure.

Explore our comprehensive directory of visa sponsorship jobs from employers worldwide who are ready to sponsor talented international professionals.

Technical Skills Required

Python Distributed Systems Machine Learning Infrastructure

Interested in opportunities specifically in United State? Discover our dedicated Visa Sponsorship Jobs in United State page featuring roles from top employers in this location.

Benefits & Perks

Equity-heavy compensation

Competitive base salary

Visa sponsorship available

Remote-first working environment

Optional access to Melbourne hub

Job Description

About the Company

Pluralis Research conducts foundational research in Protocol Learning, an approach to training foundation models across multiple participants without requiring any single participant to hold a complete copy of the model.

The company is developing technology designed to enable community-trained and community-owned frontier models through decentralized machine learning infrastructure and sustainable economic models.

Pluralis Research is backed by leading investors and brings together experienced machine learning researchers and distributed systems engineers from major technology companies and innovative startups.

About the Role

Want the full job description? Read the complete details on LinkedIn, the original posting.

Continue on LinkedIn

This is a short excerpt. All rights to the full description belong to its original publisher.