Role Overview
A Machine Learning Evaluation Specialist is needed to develop and assess advanced, research-oriented problems that test the limits of artificial intelligence systems. This fully remote position demands deep subject-matter expertise and the ability to create evaluation tasks that go beyond standard machine learning workflows.
Key Responsibilities
- Formulate original, research-level machine learning challenges grounded in specialized domain knowledge
- Create evaluation frameworks that require insight beyond typical ML pipelines
- Review AI-generated responses for technical correctness, innovation, and sound methodology
- Identify and articulate specific shortcomings in proposed solutions
- Document the complexity of each problem, required expertise, and anticipated failure patterns
Qualifications
Candidates must demonstrate advanced understanding in a scientific or technical field connected to machine learning. A graduate degree (MS or PhD preferred) is required. You should have hands-on familiarity with core ML practices such as model selection, feature engineering, and performance evaluation.
You must be deeply aware of current research frontiers in your domain—the kind of knowledge that reveals where conventional AI approaches break down. Exceptional written communication skills are essential for clearly explaining complex problems and critiques.
This role requires self-direction and the ability to thrive on intellectually rigorous, independent work.
Work Structure
This is a freelance, project-based contract position with no guaranteed hours. Work is conducted remotely on an independent contractor (1099) basis. Candidates must pass an evaluation task to qualify for paid work. Weekly availability ranges from 10 to 40 hours, depending on project needs.
Compensation
Hourly rates range from $200 to $400, based on domain specialization and experience level. Work is offered on a per-project basis with flexible scheduling.
