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AI Distributed Training Fault Tolerance Engineer

David Dubois

Full-time · Job · Los_Angeles

About the role

Have you ever debugged a distributed training job that failed at step 47,832 of 50,000 and lost 40 hours of gradient accumulation? We build the infrastructure that makes that scenario impossible. Mivex runs one of the largest AI training cluster scheduling systems outside the hyperscalers. Our customers are mid-market ML teams who can't afford an in-house infrastructure team but need GPU-efficient, fault-tolerant training at scale. Fault tolerance is the feature they ask about most. You'd join our core platform team of 6 and own the fault detection and recovery subsystem. This means designing checkpoint strategies, implementing failure classification, and building automatic restart logic that preserves training state with minimal compute waste. The work is low-level, high-impact, and requires deep knowledge of how PyTorch distributed and NCCL actually behave under failure conditions.

Responsibilities

  • Design and implement checkpoint strategies for distributed training workloads
  • Build failure classification systems that distinguish recoverable from non-recoverable faults
  • Implement automatic restart and step recovery logic across multi-node training setups
  • Benchmark fault recovery overhead against training throughput across job sizes
  • Collaborate with cluster scheduling engineers to integrate fault signals into scheduling decisions

Requirements

  • 6+ years in ML infrastructure or systems engineering
  • Deep knowledge of PyTorch distributed (DDP, FSDP) and NCCL
  • Experience with Kubernetes-based GPU cluster management
  • Ability to debug low-level distributed training failures
  • Prior work on checkpoint systems or fault-tolerant distributed systems preferred

Benefits

  • $200k+ base + equity
  • Fully remote
  • $10k annual hardware and tooling budget
  • Top-tier health and dental coverage
  • Quarterly infrastructure deep-dive retreats

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Categories

MLOps & AI Infrastructure AI & Machine Learning Engineers

Skills

python pytorch kubernetes aws gcp

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$200k+ / year

AI Expertise

MLOps & AI Infrastructure AI & Machine Learning Engineers

Skills

python pytorch kubernetes aws gcp docker mlflow

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