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The company is looking to enhance the efficiency and scalability of its machine learning model training process.

Requirements

• Experience with both ML Platforms and building ML-based applications
• Experience building scalable, reliable infra at a fast-paced environment
• Experience with model training, model optimization, or large data processing pipelines
• Machine Learning Expertise is preferred but not necessary
• Knows how to push the GPU to its limit from Python to CUDA kernel level
• Built the inference or training loop for a large model (ideally with LLM flavor)
• Knows how to write (readable) high performance C++

Responsibilities

• Setup efficiency monitoring for all training jobs to identify models that need improvement
• Work with customer teams to benchmark/profile their jobs and make improvements
• Create standardized APIs for stack-wide abstractions like training datasets, bulk inference jobs, evaluation metrics
• Optimize dataloaders / training data formats to ensure high gpu utilization
• Optimize distributed training configurations (network topologies, sharding strategies, pipelines, etc)

Other

• High customer empathy, able to communicate with customers well
• Comfortable reading papers / keeping up with SOTA ML literature
• 5+ years as a SWE, ideally building infrastructure/customer facing product, experience in AV or robotics is also great
• U.S. person status, and/or citizenship status may be required for this position