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Machine Learning Research Engineer (Remote | )

Remote · Ghana Full-time

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. Application Process Apply for the role and complete the screening questions. Complete an AI interview of approximately 30 minutes. Complete the hiring manager review. If selected, complete onboarding and begin the first task within 24–48 hours.

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