ML Researcher (Remote | $150-$200/hr)

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.