Distributed ML Platform Engineer (Remote)

Pluralis Research; California; Remote; USD 120,000 - 170,000; Full time

Benefits offered by this job

Equity-heavy package

Remote-first culture

Visa sponsorship and relocation

Job summary

Pluralis Research is seeking an experienced infrastructure engineer to design and scale the platform for Protocol Learning across consumer-grade hardware and cloud resources.

You will manage multi-cloud deployments (AWS/GCP/Azure), distributed training pipelines, and real-time networking, ensuring fault tolerance and high availability for ongoing experimentation.

The role emphasizes remote-first collaboration, strong SRE practices, and ownership of the stack from orchestration to observability.

Qualifications

• Experience designing multi-cloud infrastructure and large-scale compute pipelines.
• Strong background in distributed ML workflows and checkpointing.
• Proficient with Python, async programming, and reliability tooling.

Responsibilities

• Architect fault-tolerant multi-cloud infrastructure for distributed ML systems.
• Build and scale GPU workloads, data streaming, and model versioning pipelines.
• Develop observability, monitoring, and incident response practices.

Skills

Infrastructure engineering

Distributed systems

Python engineering

Observability

SRE practices

Startup experience

Education

Bachelor's degree in Computer Science or similar

Tools

Pulumi

Terraform

Docker

Kubernetes

NVIDIA runtime

Prometheus/Grafana

Cloud SDKs

Job description

Pluralis Research is seeking an experienced infrastructure engineer to design and scale the platform for Protocol Learning across consumer-grade hardware and cloud resources.

You will manage multi-cloud deployments (AWS/GCP/Azure), distributed training pipelines, and real-time networking, ensuring fault tolerance and high availability for ongoing experimentation.

The role emphasizes remote-first collaboration, strong SRE practices, and ownership of the stack from orchestration to observability.