Machine Learning Research Scientist (Remote | $60–$120/hr)

Synthires; San Francisco (CA); Remote; USD 83,000 - 165,000; Part time

Job summary

Synthires is seeking an experienced ML Engineer (MSc/PhD) for remote, part-time engagement. The role focuses on developing ML models, training pipelines, and inference systems, with strong emphasis on Python and reproducible workflows.

Ideal candidates have advanced degrees in CS/ML/AI, substantial ML experience, and the ability to implement and debug complex workflows across a coding-centric environment. Flexible remote work worldwide with approximately 15 hours per week.

Qualifications

• Master's degree or PhD in CS/ML/AI or related quantitative field.
• Strong professional or research experience in machine learning.
• Proficiency in Python and experience using coding agents.
• Ability to implement, debug, and validate complex ML workflows.

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.

Skills

Python

Machine Learning

Coding agents

Education

MSc/PhD in CS/ML/AI

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.