ML Engineer (Remote | $60–$120/hr)

Synthires; Greater London; Remote; GBP 62,000 - 124,000; Part time

Job summary

Synthires is seeking an experienced ML Engineer (MSc or PhD) for a remote contractor role. The position focuses on model development, training and inference systems, with a heavy emphasis on Python coding and reproducible workflows.

Responsibilities include building and validating models and pipelines, implementing components and numerical methods, creating reproducible workflows, and optimizing memory and performance.

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.
• Proficiency in Python and experience using coding agents.
• Ability to implement, debug, and validate complex machine learning 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

Data pipelines

Research skills

Coding agents

Education

Master's degree or PhD

Tools

Git

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.