Research Engineer - Distributed Training
P
Prime IntellectAI/ML
United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- English
- Experience
- Extensive experience
- Required Skills
- PythonSoftware DevelopmentArtificial IntelligenceCloud ComputingMachine LearningPyTorchCI/CD
Requirements
- Extensive experience in designing and implementing end-to-end pipelines for training and deploying large-scale AI models
- Deep expertise in distributed training techniques, frameworks (PyTorch Distributed, DeepSpeed, MosaicML’s LLM Foundry), and tools (Ray)
- Experience in large-scale model training including data, tensor & pipeline parallelism
- Solid understanding of MLOps best practices (model versioning, experiment tracking, CI/CD)
- Passion for advancing decentralized AI model training and democratizing AI capabilities
Responsibilities
- Lead and participate in novel research for decentralized training orchestration
- Optimize AI workload performance, cost, and resource utilization
- Contribute to open-source libraries and frameworks for distributed model training
- Publish research in top-tier AI conferences
- Distill technical project outcomes into layman approachable technical blogs
- Stay up-to-date with AI/ML infrastructure, tools, and decentralized training research
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