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# ML Infrastructure Engineer

- **Company:** Finoit Inc
- **Location:** Redwood City, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Computer Clusters, Distributed Computing Environment, Distributed Systems, Memory Management, Job Scheduling, Machine Learning, Performance Tuning, Google Cloud, Pytorch, Containerization, Kubernetes, Slurm, Machine Learning Operations, TensorRT, Data Pipelines
- **Published:** August 6, 2026
- **Apply:** https://www.dice.com/job-detail/36a10000-c41f-4113-933d-a1e87110a363

## About the Role

* 7+ years of experience in ML Infrastructure, HPC, or Distributed Systems.
 * Strong experience with PyTorch, DeepSpeed, FSDP, ZeRO, or similar distributed training frameworks.
 * Hands-on experience with Kubernetes, cloud platforms (AWS/Google Cloud Platform), and containerized environments.
 * Strong understanding of distributed systems, GPU optimization, NCCL, memory management, and performance tuning.
 * Experience building scalable ML infrastructure from development through production., * Experience with multimodal AI, robotics data pipelines, Triton, TensorRT, custom ML kernels, or ML compiler/runtime optimization.

## Description

* Design and scale distributed ML training infrastructure for large GPU clusters.
 * Build and optimize training pipelines using PyTorch, DeepSpeed, and distributed training frameworks.
 * Develop and maintain job scheduling systems using Kubernetes and/or SLURM.
 * Create high-throughput data pipelines for large-scale multimodal datasets.
 * Optimize GPU utilization, memory efficiency, and overall system performance.
 * Build low-latency inference pipelines for production ML deployments.


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