Machine Learning Engineer – ML Training Platform

🕒 April 1

🏄 California – Remote

🏄 California – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

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Pluralis Research

WebsiteLinkedInAll Job Openings

1 - 10 employees

🤖 Artificial Intelligence

🌐 Web 3

Artificial Intelligence • Web 3

Pluralis Research is a foundational AI research lab focused on Protocol Learning — decentralized, multi‑participant training of foundation models where no single participant holds a full copy of the model. The group develops methods to enable communication‑efficient model and pipeline parallelism, unextractable collaborative models, and high‑compression context parallelism so community‑trained, community‑owned frontier models can scale over low‑bandwidth, internet‑connected devices. Their work targets practical systems and algorithms that make decentralized training competitive with centralized training while enabling new ownership and economic models.

📋 Description

• Architect, build, and scale the foundational infrastructure powering our decentralized ML training platform • Design resource management systems provisioning and orchestrating compute across AWS, GCP, and Azure using infrastructure-as-code (Pulumi/Terraform) • Handle dynamic scaling, state synchronization, and concurrent operations across hundreds of heterogeneous nodes • Architect fault-tolerant infrastructure for distributed ML including GPU clusters, health monitoring, and resilient retry strategies • Build systems that simulate and handle real-world network conditions

🎯 Requirements

• 5+ years of work experience with deep experience in infrastructure & platform engineering • Production experience with infrastructure-as-code (Pulumi/Terraform/CloudFormation) managing multi-cloud deployments • Lifecycle orchestration, self-healing systems, Docker/Kubernetes (EKS), GPU workloads, and heterogeneous clusters at scale • Deep understanding of distributed training workflows, checkpointing, data sharding, model versioning, long-running job orchestration, decentralized networking • Strong Python engineering (asyncio, concurrency, retry logic, cloud SDKs, CLI tooling) • Hands-on experience in observability, SRE practices, monitoring (Prometheus/Grafana), performance profiling, and incident response • Experience in a startup environment with an emphasis on micro-services orchestration or big tech background • Deep understanding of multi-cloud infra & distributed training systems

🏖️ Benefits

• Pluralis will provide visa sponsorship and relocation support to exceptional candidates for both US and Australia