Distributed Training (Jaipur)
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Jaipur, India
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Posted: a week ago
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- Enhance performance of distributed training frameworks such as PyTorch, DeepSpeed, or similar systems
- Identify and resolve bottlenecks in large-scale training pipelines (e.g., memory usage, communication overhead, GPU utilization)
- Optimize inference systems using techniques like quantization, caching, and batching to achieve low latency and high throughput
- Collaborate with infrastructure and platform teams to improve resource orchestration, scheduling, and system reliability
- Design benchmarking tools and metrics to measure training efficiency, system throughput, and latency performance
- Apply advanced optimization techniques (e.g., mixture-of-experts, speculative decoding, model parallelism) to improve large model performance
- Continuously evaluate new approaches to hardware acceleration and model execution efficiency
Required Qualifications
- 3+ years of hands-on experience optimizing GPU-based machine learning workloads
- Strong expertise in deep learning frameworks such as PyTorc Apply on Kit Job: kitjob.in/job/4lp6el
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Company nameGoogle
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Job positionDistributed Training (Jaipur)
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