Machine Learning Engineer - ML Training Platform
AI
Pluralis Research is seeking a Machine Learning Engineer to architect and scale the ML training platform for Protocol Learning, training large models on decentralized consumer devices. The role involves multi-cloud infrastructure, distributed training systems, and real-world networking. Requires strong infrastructure-as-code, distributed systems, and Python engineering experience.
What you'll do
- Design resource management systems that provision and orchestrate compute across AWS, GCP, and Azure with 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, NVIDIA runtime, S3 checkpointing, large-dataset management and streaming, health monitoring, and resilient retry strategies
What you need
Must-have
PulumiTerraformCloudFormationAWSGCPAzureDockerKubernetes
Nice-to-have
Foundation model pre-trainingPost-trainingReinforcement Learning
Soft skills
Mission alignmentComfortable working across timezonesProfessional-level English proficiency
Machine Learning EngineerML Training PlatformDistributed SystemsInfrastructureMulti-cloudProtocol LearningDecentralized AIPythonKubernetesRemote