Pluralis Research
Machine Learning Engineer - ML Training Platform
- Confirmed live in the last 24 hours
- No salary listed
- Mid level
- Full-time
- Remote · San Francisco
- Added 1 month ago
About this role
Pluralis Research is seeking a Machine Learning Engineer to build and scale a platform for decentralized model training on consumer-grade devices. This role focuses on architecting robust, multi-cloud infrastructure and distributed systems capable of handling real-world network conditions. The ideal candidate will be passionate about Protocol Learning and thrive in a fast-paced, remote-first startup environment.
What you'll do
- Design resource management systems across AWS, GCP, and Azure.
- Architect fault-tolerant infrastructure for distributed ML training.
- Build systems to simulate and handle real network conditions (bandwidth shaping, latency).
- Manage node churn and ensure data flow across heterogeneous networks.
- Implement infrastructure-as-code using Pulumi or Terraform.
- Develop robust retry strategies and health monitoring.
What they're looking for
- Infrastructure-as-Code (Pulumi/Terraform)
- Docker/Kubernetes (EKS)
- GPU Workloads
- Distributed Systems
- Python (asyncio, concurrency)
- Prometheus/Grafana
- Networking (P2P, NAT traversal)
- Cloud SDKs
Benefits
- Equity-Heavy Package
- Remote-First Culture
- Visa Sponsorship (Australia or US)
- Relocation Support (Australia or US)
- Flexible work environment
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Pluralis Research
Likely interview questions
- Describe your experience with infrastructure-as-code tools like Pulumi or Terraform, and a specific challenge you overcame.
- Explain your understanding of distributed training workflows, including checkpointing and data sharding.