

Crossing Hurdles
Machine Learning Engineer | $30/hr Remote | Mercor
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer, offering $25–$30/hr on a remote contract basis in India, requiring expertise in Reinforcement Learning, Python, and benchmarking methodologies, with a commitment of 10–40 hours/week.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
240
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🗓️ - Date
December 2, 2025
🕒 - Duration
Unknown
-
🏝️ - Location
Remote
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#ML (Machine Learning) #Reinforcement Learning #AI (Artificial Intelligence) #PyTorch #Python #Programming #Documentation #TensorFlow #Computer Science
Role description
At Crossing Hurdles, we work as a referral partner. We refer candidates to Mercor that collaborates with the world’s leading AI research labs to build and train cutting-edge AI models.
Organization: Mercor
Position: Technical Reviewer – RL Environment Terminal Benchmarking (Agentic AI)
Referral Partner: Crossing Hurdles
Type: Hourly Contract
Compensation: $25–$30/hour
Location: India (Remote)
Commitment: 10–40 hours/week
Role Responsibilities (Training support will be provided)
• Review and validate reinforcement learning (RL) environment design, terminal conditions, and benchmarking protocols.
• Assess evaluation metrics and ensure fairness, reproducibility, and consistency across RL experiments.
• Provide detailed technical feedback on environment codebases, documentation, and evaluation workflows.
• Collaborate with AI researchers to refine environment architecture, performance measures, and reproducibility standards.
• Verify experimental results across runs, seeds, and hardware configurations to ensure robust benchmarking practices.
• Recommend improvements for environment design, metric definitions, and implementation rigor.
Requirements
• Strong background in Reinforcement Learning, Computer Science, or Applied AI research.
• Experience working with RL environments and benchmarking methodologies.
• Skilled in Python programming; familiarity with frameworks such as PyTorch or TensorFlow preferred.
• Excellent understanding of evaluation metrics, reproducibility protocols, and experimental analysis.
• Strong analytical thinking, technical communication, and attention to detail.
• Interest in agentic AI systems and the development of reliable evaluation pipelines.
Application Process (Takes 20 min)
1. Upload resume
1. AI interview based on your resume (15 min)
1. Submit form
At Crossing Hurdles, we work as a referral partner. We refer candidates to Mercor that collaborates with the world’s leading AI research labs to build and train cutting-edge AI models.
Organization: Mercor
Position: Technical Reviewer – RL Environment Terminal Benchmarking (Agentic AI)
Referral Partner: Crossing Hurdles
Type: Hourly Contract
Compensation: $25–$30/hour
Location: India (Remote)
Commitment: 10–40 hours/week
Role Responsibilities (Training support will be provided)
• Review and validate reinforcement learning (RL) environment design, terminal conditions, and benchmarking protocols.
• Assess evaluation metrics and ensure fairness, reproducibility, and consistency across RL experiments.
• Provide detailed technical feedback on environment codebases, documentation, and evaluation workflows.
• Collaborate with AI researchers to refine environment architecture, performance measures, and reproducibility standards.
• Verify experimental results across runs, seeds, and hardware configurations to ensure robust benchmarking practices.
• Recommend improvements for environment design, metric definitions, and implementation rigor.
Requirements
• Strong background in Reinforcement Learning, Computer Science, or Applied AI research.
• Experience working with RL environments and benchmarking methodologies.
• Skilled in Python programming; familiarity with frameworks such as PyTorch or TensorFlow preferred.
• Excellent understanding of evaluation metrics, reproducibility protocols, and experimental analysis.
• Strong analytical thinking, technical communication, and attention to detail.
• Interest in agentic AI systems and the development of reliable evaluation pipelines.
Application Process (Takes 20 min)
1. Upload resume
1. AI interview based on your resume (15 min)
1. Submit form






