Description review
AI/ML Engineer - Fully Remote | Upto $85/hr
mercor · India · back to the listing
HR standards
81/100
solid
Title ↔ description
72/100
solid
Reads as
Machine Learning Engineer
99% confident
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
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What the listing never says
- 17 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
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 Engineer (Coding Agent Experience)
Type:Contract
Compensation:$85/hour
Location:Remote
Role Responsibilities
• Use frontier AI coding agents to complete and evaluate complex machine learning and AI engineering tasks.
• Review model-generated implementations involving model training, inference systems, MLOps, and LLM applications.
• Identify bugs, edge cases, performance issues, and failure modes in AI models.
• Compare outputs from multiple frontier models and assess their strengths and weaknesses.
• Apply professional engineering judgment to realistic ML engineering scenarios.
Qualifications
Must-Have
• 2+ years of professional machine learning engineering experience.
• Experience building production ML systems, model deployment infrastructure, LLM applications, or AI-powered products.
• Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
• Ability to evaluate model-generated machine learning implementations and technical tradeoffs.
Preferred
• Experience deploying ML systems to production.
Compensation & Legal
• $400 per accepted task
• Compensation is tied to accepted work.
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
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 Engineer (Coding Agent Experience)
Type:Contract
Compensation:$85/hour
Location:Remote
Role Responsibilities
• Use frontier AI coding agents to complete and evaluate complex machine learning and AI engineering tasks.
• Review model-generated implementations involving model training, inference systems, MLOps, and LLM applications.
• Identify bugs, edge cases, performance issues, and failure modes in AI models.
• Compare outputs from multiple frontier models and assess their strengths and weaknesses.
• Apply professional engineering judgment to realistic ML engineering scenarios.
Qualifications
Must-Have
• 2+ years of professional machine learning engineering experience.
• Experience building production ML systems, model deployment infrastructure, LLM applications, or AI-powered products.
• Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
• Ability to evaluate model-generated machine learning implementations and technical tradeoffs.
Preferred
• Experience deploying ML systems to production.
Compensation & Legal
• $400 per accepted task
• Compensation is tied to accepted work.
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