Ai Research Expert - Fully Remote | Upto $145/Hr

Mercor; San Francisco (CA); Hybrid; GBP 115,000 - 151,000; Full time

Job summary

Mercor seeks a PhD-level ML researcher for a remote contract role evaluating AI-generated content and ML research for model improvement. You will develop evaluation metrics and work with AI teams to enhance data quality, training methods, and downstream performance.

Ideal candidates have publications at ICML/NeurIPS/ICLR and a strong track record in ML research. Start is urgent, with contract terms paying $110–$145 per hour on a remote basis.

Qualifications

• PhD in ML/CS/AI or related field required.
• At least one main conference paper at ICML/NeurIPS/ICLR; preference for 2+ publications.
• Experience conducting original ML research and evaluating AI systems.

Responsibilities

• Evaluate accuracy and depth of AI-generated content to improve model outputs.
• Review machine learning research for alignment with domain principles.
• Provide clear, structured feedback to AI research teams to improve data and performance.
• Develop evaluation rubrics and benchmarks for AI-generated tasks.
• Collaborate with subject matter experts to ensure dataset relevance and coverage.
• Work independently and asynchronously to meet deadlines.

Skills

ML research

Academic writing

Rigorous evaluation

Independent work

Education

PhD in Machine Learning

Publications at ICML/NeurIPS/ICLR

2+ publications at venues

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: ML Research PhD Experts (ICML / NeurIPS / ICLR Publications)
Type: Contract
Compensation: $110–$145/hour
Location: Remote

Role Responsibilities

• Evaluate the accuracy and depth of AI-generated content to strengthen reasoning and rigor in model outputs.
• Review complex machine learning research for alignment with domain principles and methodologies.
• Provide clear, structured feedback to AI research teams to improve training data quality and downstream performance.
• Develop evaluation rubrics and benchmarks for assessing AI-generated tasks and solutions.
• Collaborate with subject matter experts to ensure consistency, relevance, and coverage across datasets.
• Work independently and asynchronously to meet deadlines while improving AI model performance.

Qualifications

Must-Have

• PhD in Machine Learning, Computer Science, AI, or a closely related field.
• Published at least one main conference paper at ICML, NeurIPS, or ICLR.
• Strong preference for candidates with 2+ publications at these venues.
• Demonstrated experience conducting original ML research.

Preferred

• Expertise in Reinforcement Learning (RL).
• Experience with Meta-Learning.
• Knowledge of Recursive Self-Improvement.
• Familiarity with AI for Science (e.g., weather forecasting, protein modeling, scientific discovery).

Start Date

• Urgent; initial data/results expected Monday / Tuesday 27th July.

Resources & Support

• For any help or support, reach out to: [e-mail]