ML Engineer

Role Overview

Contribute to advanced AI training work by building, solving, reviewing, and validating challenging machine-learning engineering tasks. This coding-intensive contract role focuses on model development, training and inference systems, numerical computing, performance optimization, and Python-based workflows.

Key Responsibilities

• Develop and validate machine-learning models, training pipelines, inference systems, and supporting infrastructure.
• Create, solve, review, and validate complex machine-learning engineering tasks.
• Implement model components, data pipelines, evaluation systems, and numerical methods.
• Build reproducible training and inference workflows using Python and command-line tools.
• Optimize memory use and throughput, troubleshoot numerical or system-level failures, and verify objective correctness and performance requirements.

Qualifications

• 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 as part of your development workflow.
• Relevant experience may include PyTorch, JAX, NumPy, SciPy, SGLang, vLLM, llama.cpp, Hugging Face Transformers, or Hugging Face Tokenizers. Equivalent tools are considered when supported by directly relevant depth.
• Experience at an established technology company, AI lab, research organization, or recognized engineering environment is strongly preferred. Exceptional open-source or academic experience may also qualify.

Work Terms

• Independent contractor role, fully remote and open globally.
• Approximately 15 hours per week.
• Flexible schedule, with the ability to choose your workdays and hours, including weekends.
• Selected candidates should be ready to begin immediately and complete their first task within 24 to 48 hours after onboarding.

Compensation

• $80 to $150 per hour.
• Compensation is output-based and paid per task that meets project specifications. Completion time varies by experience and workflow, and minimum submission requirements apply.

Application Process

• Apply and complete screening questions.
• Complete an AI interview of approximately 30 minutes.
• Proceed through hiring-manager review.
• Applicants acknowledge the applicable candidate terms and privacy policy as part of the application process.