AI/ML Research Scientist (Remote | $60–$120/hr)

Synthires; United States; Remote; AUD 118,000 - 235,000; Part time

Job summary

Synthires is seeking an experienced ML Engineer (MSc or PhD) for a remote, worldwide contractor role. You will develop and optimize machine learning models, training pipelines, and inference systems with a strong focus on Python and reproducible workflows.

The role is coding-intensive, involving building and validating ML workflows and tooling. The position requires about 15 hours per week with flexible scheduling and immediate availability preferred; first task expected within 24–48 hours after

Qualifications

• Master's degree or PhD in Computer Science or related quantitative field.
• Strong professional or research experience in machine learning.
• Proficiency in Python and experience with coding agents.

Responsibilities

• Develop and validate ML models, training pipelines, and inference systems.
• Implement components, data pipelines, evaluation systems, and numerical methods.
• Build reproducible workflows using Python and command-line tools.
• Debug numerical and system-level issues and optimize memory usage and performance.
• Create, solve, review, and validate challenging ML engineering tasks.

Skills

Python

Machine Learning

Numerical methods

Data pipelines

Reproducible workflows

Education

Master's degree or PhD in Computer Science/ML or related

Tools

Command-line tools

Job description

ML Engineer (MSc. or PhD) (Remote | $60–$120/hr)

Position: ML Engineer (MSc. or PhD)

Type: Contractor (Part-Time, approximately 15 hours/week)

Compensation: $60–$120/hour

Location: Remote (Worldwide)

About the Opportunity

This opportunity is for experienced Machine Learning Engineers to contribute to AI training projects involving model development, training and inference systems, and performance optimization. The role is highly coding-intensive, with a focus on Python, reproducible workflows, and coding agents.

Key Responsibilities

• Develop and validate machine learning models, training pipelines, and inference systems.
• Implement model components, data pipelines, evaluation systems, and numerical methods.
• Build reproducible workflows using Python and command-line tools.
• Debug numerical and system-level issues and optimize memory usage and performance.
• Create, solve, review, and validate challenging machine learning engineering tasks.

Required Qualifications

• Master's degree or PhD in Computer Science, Machine Learning, AI, Applied Mathematics, Statistics, Engineering, or a related quantitative field.
• Strong professional or research experience in machine learning.
• Practical proficiency in Python and experience using coding agents.
• Ability to implement, debug, and validate complex machine learning workflows.

Preferred Qualifications

• Experience at an established technology company, AI laboratory, or research organization.
• Exceptional academic or open-source engineering experience demonstrating relevant expertise.

Compensation

• $60–$120/hour, with output-based payment for tasks meeting project specifications.
• Approximately 15 hours per week with a flexible schedule.
• Immediate availability preferred; first task expected within 24–48 hours after onboarding.