Remote-Ready ML Systems Engineer: High-Throughput Training

United States Digital Space LLC; United States; Hybrid; USD 120,000 - 160,000; Full time

Job summary

AD Inc. is seeking a Machine Learning Systems Engineer to join the ML Acceleration team. You will own core systems enabling researchers to train frontier models at scale, focusing on speed, cost, reliability, and throughput.

The role involves profiling, kernel development, and data-pipeline optimization to push the efficiency of large-scale distributed model training and shorten convergence times.

Qualifications

• Bachelor's, Master's degree, or PhD in Computer Science, Computer Engineering, or related technical discipline.
• Strong proficiency in Python.
• Extensive hands-on experience with PyTorch.
• Experience optimizing ML model execution during training and inference; solid ML concepts and architectures.

Responsibilities

• Performance profiling and optimization to reduce step time.
• Optimize distributed training pipelines using frameworks like PyTorch Distributed.
• Design and maintain high-performance GPU kernels in Triton or CUDA.
• Build and optimize robust data loading pipelines for training throughput.

Skills

Python

PyTorch

Problem solving

Analytical thinking

Education

Bachelor's/Master's/PhD in CS/CE

Tools

Nsight

PyTorch Profiler

CUDA

Triton

Job description

AD Inc. is seeking a Machine Learning Systems Engineer to join the ML Acceleration team. You will own core systems enabling researchers to train frontier models at scale, focusing on speed, cost, reliability, and throughput.

The role involves profiling, kernel development, and data-pipeline optimization to push the efficiency of large-scale distributed model training and shorten convergence times.