Remote ML Researcher & Scientist — Part-time Contractor

SaidGig; United States; Remote; USD 83,000 - 165,000; Part time

Job summary

SaidGig is seeking a technically skilled contractor to contribute to challenging AI training work, focusing on model development, training and inference systems, numerical computing, and Python-based workflows.

Responsibilities include developing and validating ML models and pipelines, implementing data components, and building reproducible training/inference workflows. The role offers flexible hours, remote work, and task-based compensation, with immediate start options.

Qualifications

• Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative field.
• Strong professional or research experience in machine learning.
• Practical proficiency in Python and experience using coding agents in a Python workflow.

Responsibilities

• Develop and validate machine learning models, training pipelines, inference systems, and supporting infrastructure.
• Create, solve, review, and validate complex machine learning engineering tasks.
• Implement or modify models, data pipelines, evaluation systems, model components, and numerical methods.
• Build reproducible training and inference workflows using Python and command line tools.
• Optimize memory use and throughput, debug numerical and system level failures, and verify objective correctness and performance requirements.

Skills

Machine Learning

Python

Numerical Computing

Performance Optimization

Education

Master's degree or PhD in Computer Science/ML/AI/Applied Math/Statistics/Engineering

Tools

Python tooling

Job description

SaidGig is seeking a technically skilled contractor to contribute to challenging AI training work, focusing on model development, training and inference systems, numerical computing, and Python-based workflows.

Responsibilities include developing and validating ML models and pipelines, implementing data components, and building reproducible training/inference workflows. The role offers flexible hours, remote work, and task-based compensation, with immediate start options.