Senior ML Engineer (MSc. or PhD)

Overview

Micro1 is looking for highly skilled machine learning experts to contribute to an AI training project focused on model development, training and inference systems, numerical computing, performance optimization, and Python. This is a coding-heavy contractor role with flexible hours and a remote global setup.

What You’ll Work On

• Develop and validate machine-learning models, training pipelines, inference systems, and supporting infrastructure.
• Implement model components, data pipelines, evaluation systems, and numerical methods.
• Build reproducible programmatic workflows using Python and command-line tools.
• Create, solve, review, and validate challenging machine-learning engineering tasks.
• Implement or modify models, construct reproducible training or inference workflows, optimize memory or throughput, debug numerical or system-level failures, and verify correctness and performance.

Requirements

• A master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline.
• Strong professional or research experience in machine learning.
• Practical proficiency with Python and coding agents.
• Equivalent tools may also be considered when the candidate demonstrates directly relevant depth.
• Experience at a well-established technology company, AI laboratory, research organization, or other recognized engineering environment is strongly preferred.
• Exceptional open-source or academic experience may also qualify.

Process

1. Apply to the role and complete the screening questions.
2. Complete an AI interview of approximately 30 minutes.
3. Complete the hiring manager review.

Additional Details

• Contractor role, approximately 15 hours per week.
• Flexible schedule; you choose the days and hours you work, including weekends if desired.
• Compensation is output-based and paid per task that meets the project specifications.
• Minimum submission requirements apply.
• The team typically fills roles within 48 hours and expects selected experts to begin their first task within 24–48 hours after onboarding.