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Egen

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ML Platform Engineer, Distributed Training

Remote
Full-Time
Posted October 26, 2026
Salary
20-35 LPA
Batches
2-4 years experience required
Apply Route
100% Direct

About The Role

Egen is a fast‑growing data‑first startup that empowers enterprises with cutting‑edge AI and cloud solutions. As an ML Platform Engineer focused on Distributed Training, you will build and scale GPU‑powered training pipelines on GKE, optimize performance, and ensure reliable production deployment for large language models. Join a collaborative team of top engineers, work remotely, and drive impactful AI innovations for global clients.

Responsibilities

Design, implement, and maintain distributed training pipelines on GKE with GPU node pools.
Optimize multi-node GPU networking (RDMA, NCCL) and troubleshoot platform failures.
Develop performance benchmarks, profiling, and cost‑optimization for large‑scale model training.
Collaborate with data scientists and client infrastructure teams to integrate ML workflows into production.
Ensure reliability, scalability, and monitoring of training jobs using tools like Ray Train, DeepSpeed, and FSDP.

Requirements

  • Strong experience with PyTorch distributed training frameworks (FSDP, DeepSpeed, Megatron, NeMo) and Ray Train.
  • Hands‑on expertise in Kubernetes (GKE), GPU node provisioning, and job scheduling.
  • Proficiency in Linux, Python, and performance profiling tools (Nsight, nvprof, TensorBoard).
  • Solid understanding of networking protocols for GPU clusters (RDMA, GPUDirect, NCCL).
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

Eligibility Checklist

B.Tech/M.Tech in Computer Science, Electrical, or related engineering

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