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

Job summary

Develop and validate machine learning models, training pipelines, inference systems, data pipelines, and evaluation systems. Build reproducible Python workflows, debug numerical and system-level issues, optimize performance and memory use, and create, solve, review, and validate machine learning engineering tasks.

Job details

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.

What you’ll do

Develop and validate machine learning models, training pipelines, inference systems, data pipelines, and evaluation systems. Build reproducible Python workflows, debug numerical and system-level issues, optimize performance and memory use, and create, solve, review, and validate machine learning engineering tasks.

Requirements

A master's degree or PhD in a relevant quantitative field and strong professional or research experience in machine learning are required. Candidates need practical Python proficiency, experience with coding agents, and the ability to implement, debug, and validate complex machine learning workflows.

Listed skills

• Machine learning · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Machine Learning
• Python
• Model Development
• Model Training
• Inference Systems
• Training Pipelines
• Data Pipelines
• Model Evaluation
• Numerical Methods
• Debugging
• Performance Optimization
• Memory Optimization
• Reproducible Workflows
• Command-Line Tools
• Coding Agents

Job areas

• Technology
• Software
• Science & Research
• Data & Analytics
• Engineering

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