Shape challenging AI research tasks using PyTorch or JAX expertise. This work emphasizes inference, evaluation, and systems thinking rather than heavy model training. As an ML research engineer, research scientist, or applied scientist, you will contribute ideas for a long-horizon project with a leading AI lab. Your work will focus on LLMs, GPU performance, reinforcement learning, or scientific ML. You will explain why each problem challenges frontier models. Key Responsibilities:

Develop plans for difficult machine learning engineering tasks Design tasks that stump frontier models Focus on inference, evaluation, and systems work Explain why problems challenge frontier models Contribute ideas without building or reviewing tasks Requirements:

Current or recent ML research role Hands-on PyTorch or JAX model experience Deep knowledge of one specified research area Ability to explain frontier model difficulty Benchmark or evaluation writing experience is advantageous Apply your PyTorch, JAX, and machine learning research expertise to frontier-model evaluation challenges.

📌 Machine Learning Research Scientist (Winnipeg)
🏢 Mercor
📍 Winnipeg