Machine Learning Engineer

About OpenTrain

OpenTrain AI is the hiring and contracting organization for this expert AI training opportunity. OpenTrain helps people build careers in AI training and data labeling, where contributors apply technical expertise to improve the systems shaping modern artificial intelligence.

• Apply through OpenTrain and contribute to a cutting-edge AI project.
• Work remotely from an eligible country with a flexible part-time schedule.
• Create a free OpenTrain account and apply in minutes.

About AI Training and Data Labeling

AI training is the human side of building artificial intelligence. In technical projects like this one, experts develop, test, review, and explain code, models, pipelines, and evaluation methods so AI systems can become more capable, reliable, and reproducible.

• Contributors help evaluate model behavior and the quality of AI-generated code.
• The work combines practical engineering judgment with structured feedback.
• AI training projects can offer flexible, remote work alongside other commitments.

The Role

As an ML Engineer, you will create, solve, review, and validate challenging machine-learning engineering tasks for an AI training project. The work focuses on machine learning systems and AI engineering, including model and pipeline development, evaluation, optimization, and technical review.

This is an expert-level contractor, part-time opportunity expected to last under one month. The expected commitment is less than 20 hours per week, and the pay range is $100 to $150 USD per hour.

• Employment type: Contractor and part time
• Experience level: Expert
• Expected commitment: Less than 20 hours per week
• Expected project duration: Under one month
• Pay: $100 to $150 USD per hour
• Eligible locations: Australia, Italy, the United States, the United Kingdom, New Zealand, and Canada

What You'll Do

You will work on technically demanding tasks that test and improve machine-learning engineering capability. Your contributions may involve implementation, analysis, review, benchmarking, debugging, and documentation across model training and inference workflows.

• Develop models and machine-learning pipelines.
• Implement model components and evaluation systems.
• Optimize training or inference for latency, throughput, memory, and hardware utilization.
• Diagnose numerical and distributed-system failures.
• Review AI-generated code for correctness, quality, and technical soundness.
• Design objective tests and benchmarks.
• Document technical decisions, trade-offs, correctness, reproducibility, and limitations.
• Create, solve, review, and validate challenging machine-learning engineering tasks.

Requirements

Applicants must hold a master's degree or PhD in computer science, machine learning, artificial intelligence, applied mathematics, statistics, engineering, or a closely related quantitative discipline. Candidates should bring strong professional or research experience in machine learning and practical Python proficiency.

You must understand training, evaluation, numerical computation, or inference and be comfortable debugging beyond surface-level APIs. The role also requires the ability to build reproducible workflows and clearly explain implementation decisions, trade-offs, and failure modes.

• Advanced degree in a relevant quantitative or technical discipline.
• Strong professional or research experience in machine learning systems and AI engineering.
• Practical proficiency with Python.
• Meaningful experience with at least two relevant frameworks or inference tools.
• Ability to discuss relevant ML Engineer experience.
• Strong accuracy and attention to detail.
• Fluent English proficiency.
• Based in Australia, Italy, the United States, the United Kingdom, New Zealand, or Canada.

Who Should Apply

This opportunity is designed for experienced machine-learning engineers and researchers who can reason beneath high-level interfaces, assess implementation quality, and communicate technical choices precisely. It is a strong fit for specialists who enjoy evaluating difficult engineering problems and improving the reliability of AI systems.

• Machine-learning engineers with strong systems or AI engineering experience.
• Researchers with practical experience building and evaluating machine-learning workflows.
• Python practitioners experienced with multiple frameworks or inference tools.
• Experts who can identify failure modes and support reproducible technical work.

How the Contract Works

The project is expected to require less than 20 hours per week and continue for under one month. Contractors will complete technical AI training tasks remotely through OpenTrain AI, subject to the role's location, language, experience, and qualification requirements.

• Review the requirements and confirm your eligible location.
• Apply through OpenTrain with details about your relevant experience.
• Discuss your machine-learning engineering background.
• Complete project work within the expected part-time schedule.
• Earn $100 to $150 USD per hour for approved contractor work.