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Expert AI Computing Researcher

3 weeks ago

Bengaluru, Karnataka, India Krutrim Full time
Key Responsibilities
  1. Distributed Training Systems Architect: Design and implement highly scalable distributed training pipelines for LLMs and frontier models, leveraging model parallelism (tensor, pipeline, expert) and data parallelism techniques.
  2. Performance Optimization Expert: Utilize deep knowledge of CUDA, C++, and low-level optimizations to enhance model training speed and efficiency across diverse hardware configurations.
  3. Cutting-Edge Techniques Implementer: Research and apply novel parallelism techniques like Flash Attention to accelerate model training and reduce computational costs.
  4. Deep Learning Framework Specialist: Demonstrate proficiency in deep learning frameworks such as PyTorch, TensorFlow, and JAX, and tailor them for distributed training scenarios.
  5. Massive Model Trainer: Work with massive models, ensuring stable and efficient training across distributed resources.
  6. Scaling Laws Analyst: Design and conduct experiments to analyze the impact of model size, data, and computational resources on model performance.

You will partner closely with research scientists and engineers to integrate research findings into production-ready training systems.