Machine Learning Engineer for AI Model Training

Join a remote talent network that connects machine learning engineers with leading AI teams for short and medium term contract work. This open application makes you eligible for future contracts that match your background and interests, including tasks that support training and evaluating AI models, building realistic task deliverables, and providing domain-specific feedback to advance cutting-edge research.

• Train, evaluate, and iterate on machine learning models.
• Create tasks, datasets, or deliverables derived from real-world scenarios.
• Provide domain-specific critique and feedback to improve model behavior and research outcomes.
• Work independently on remote, project-based assignments and collaborate with project teams as required.

• Professional experience in machine learning model development.
• Proficiency in Python and common ML frameworks, such as PyTorch or TensorFlow.
• Experience with model deployment and MLOps practices.
• Strong written and verbal communication skills.
• Ability to work independently in a remote environment and manage your own schedule.

• Location: Remote.
• Engagement type: Hourly contract opportunities.
• Typical time commitment: Projects commonly require 15 to 30 hours per week, though scope and duration vary.
• Opportunities are offered on a rolling basis as projects become available.

• Pay range: $70 to $250 per hour, depending on the project and required expertise.

This is an open application to join the talent network, not a single job posting. To become eligible for project matches you will:

• Complete a one-time profile, including uploading your resume and confirming your work location.
• Undergo a credential review and an AI interview; passing these steps qualifies you for relevant projects.
• Be matched to projects on a rolling basis, and receive invitations to interview for individual opportunities that align with your skills and availability.

Once matched and selected for a project, you will work remotely on contract, set your own schedule within the project requirements, and receive the advertised hourly compensation.