Description review

ML Research Scientist - PhD

mercor · France · back to the listing

HR standards

77/100

solid

Title ↔ description

62/100

needs work

Reads as

Unclear

no confident match

What this role officially is

data scientist — ESCO, the EU occupation classification

Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.

Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist

How others title the same work

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Startups

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What the listing never says

  • 20 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

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:$60–$100/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).

• Knowledge of Meta-Learning.

• Experience with Recursive Self-Improvement.

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

Start Date

• Urgent; applications reviewed on a rolling basis.

Application Process (Takes 20–30 mins to complete)

• Upload resume

• AI interview based on your resume

• Submit form

Resources & Support

• For details about the interview process and platform information, please check:

• For any help or support, reach out to:

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

Originally posted on Himalayas

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 8 points (from 85 before penalties). Reviewed 21 Sep 2026.