Job Description

Machine Learning Expert (Remote | $150–$200/hr)

Position: Machine Learning Expert

Type: Hourly Contract

Compensation: $150–$200 per hour

Location: Remote

About the Opportunity

This opportunity is for experienced machine learning research engineers, research scientists, and applied scientists to contribute challenging machine learning engineering task ideas for a long-horizon AI research project with a leading AI lab. The focus is on designing problems that test the limits of frontier AI models, particularly in inference, evaluation, and systems engineering.

Key Responsibilities

• Develop ideas for challenging machine learning engineering tasks for an AI research project.
• Design problems that are difficult for frontier models to solve consistently.
• Focus on inference, evaluation, and systems engineering, with tasks involving both GPU and CPU workloads.
• Explain clearly why each proposed problem is challenging for advanced AI models.
• Contribute task concepts without needing to build or review the tasks themselves.

Required Qualifications

• Current or recent experience as an ML research engineer, research scientist, or applied scientist.
• Hands-on experience personally training, fine-tuning, or optimizing models using PyTorch or JAX.
• Deep knowledge of at least one of the following areas:
• Large language models (LLMs), including pretraining, alignment, and evaluations.
• GPU inference and performance, including vLLM, Triton, CUDA, or profiling.
• Reinforcement learning (RL).
• Scientific machine learning, including weather, climate, physics, or biology.
• Ability to explain why specific machine learning problems are difficult for frontier models.

Preferred Qualifications

• Experience developing benchmark or evaluation questions.
• PhD in machine learning, computer science, or physics, or an MSc with strong research output.
• Relevant research publications.
• Previous Mercor contract experience with strong performance.

Compensation

• $150–$200 per hour.
• Remote hourly contract engagement.

Application Process

The application process was not specified in the provided listing.

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