ML Engineer (MSc. or PhD)

Engineering work

Create, solve, review, and validate challenging machine learning tasks for an AI training project. Work spans model development, numerical computing, training and inference systems, performance optimization, and Python.

A task may involve modifying a model, building a reproducible workflow, reducing memory use, improving throughput, or debugging numerical and system failures. Completed implementations must satisfy objective correctness and performance requirements.

Responsibilities

• Develop and validate models, training pipelines, inference systems, and supporting infrastructure.
• Implement model components, data pipelines, evaluation systems, and numerical methods.
• Build reproducible workflows with Python and command-line tools.
• Work extensively with code and coding agents in Python.

Qualifications

• A master's degree or PhD in computer science, machine learning, AI, applied mathematics, statistics, engineering, or a related quantitative discipline.
• Strong professional or research experience in machine learning and practical proficiency with Python and coding agents.
• Relevant depth with equivalent tools may also be considered.
• Experience at an established technology business, AI lab, research organization, or recognized engineering environment is strongly preferred; exceptional academic or open-source experience may also qualify.

Schedule, payment, and selection

This worldwide remote contract calls for approximately 15 hours a week. You choose your hours and days, including weekends.

The advertised range is $60 to $120 per hour, while actual compensation is per task that meets project specifications. Completion time varies by experience and workflow, and minimum submission requirements apply.

Selection includes screening questions, an AI interview lasting about 30 minutes, and hiring manager review. Immediate availability is preferred, with selected contributors expected to begin their first task within 24 to 48 hours after onboarding.