ML Research Scientist - PhD

Mercor; New York (NY); On-site; USD 140,000 - 220,000; Full time

Job summary

Mercor is assembling a small group of world-class machine learning researchers for an initial pilot. This is a high-priority engagement with an accelerated timeline, so exceptional candidate quality and fast turnaround are critical.

We seek researchers with demonstrated frontier ML contributions, particularly those driving algorithmic innovation rather than applied analytics. A strong publication record at ICML, NeurIPS, or ICLR is preferred, with a preference for 2+ publications at these venues.

Qualifications

• PhD in ML/CS/AI or 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.

Responsibilities

• Advance state-of-the-art ML through publications and research contributions.
• Contribute to frontier ML research initiatives and algorithmic innovation.

Skills

Frontier ML research

Publications in ICML/NeurIPS/ICLR

Original ML research

Fast turnaround

Education

PhD in ML/CS/AI

Job description

Overview

We're looking to rapidly assemble a small group of world-class machine learning researchers for an initial pilot. This is a high-priority engagement with an accelerated timeline, so both exceptional candidate quality and fast turnaround are critical. We're specifically seeking researchers with demonstrated contributions to frontier ML research, particularly those driving algorithmic innovation rather than applied analytics.

Candidate Requirements

Required Qualifications

• 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 Research Areas

• Reinforcement Learning (RL)

• Meta-Learning

• Recursive Self-Improvement

• AI for Science (e.g. weather forecasting, protein modeling, scientific discovery)

Timeline

Priority: Urgent

Expected Schedule

• Initial data/results: Monday / Tuesday 27th July

Success Criteria

Candidates should have a proven record of advancing state-of-the-art machine learning through publications at top-tier conferences and possess deep expertise in frontier ML research. Speed of sourcing is important, but quality should not be compromised.