Machine Learning Engineer

Motional AD Inc.; United States; Hybrid; USD 110,000 - 170,000; Full time

Job summary

Motional AD Inc. seeks a full-time Machine Learning Systems Engineer to optimize high-performance ML systems.

The role focuses on enhancing distributed training pipelines, developing efficient GPU kernels, and improving data loading, with the option to work remotely or in-office locations in Boston, Pittsburgh, or Las Vegas. The ideal candidate has advanced degrees in a related field, strong Python skills, and extensive PyTorch experience to push the performance of ML workloads during training

Qualifications

• Bachelor's, Master's, or PhD in CS/CE or related field.
• Strong proficiency in Python.
• Extensive hands-on experience with PyTorch.
• Experience optimizing ML model training and inference.
• Analytical skills with a data-driven approach to problem-solving.

Responsibilities

• Profile ML systems to identify performance bottlenecks.
• Optimize distributed training pipelines using PyTorch Distributed.
• Design and maintain high-performance GPU kernels for ML workloads.

Skills

Python programming

Analytical skills

Data-driven problem solving

ML system optimization

Education

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

Tools

PyTorch

Profiling tools

Job description

Focusing on optimizing high-performance systems for machine learning, the full-time Machine Learning Systems Engineer will enhance distributed training pipelines, develop GPU kernels, and improve data loading processes, with the flexibility to work remotely or in-office at locations in Boston, Pittsburgh, or Las Vegas.

Key responsibilities

• Utilize profiling tools to identify and resolve performance bottlenecks in machine learning systems
• Optimize distributed training pipelines using frameworks such as PyTorch Distributed
• Design and maintain high-performance GPU kernels for advanced machine learning workloads

Required qualifications

• Bachelor's, Master's degree, or PhD in Computer Science, Computer Engineering, or a related technical discipline
• Strong proficiency in Python programming
• Extensive hands-on experience with PyTorch
• Experience in optimizing machine learning model execution during training and inference
• Exceptional analytical skills with a data-driven approach to problem-solving