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.

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