Build scalable LLM systems with Python and PyTorch at Cerebras, applying machine learning research to high-performance training and inference workflows. As an Applied Machine Learning Research Scientist, you will turn contemporary machine learning techniques into production-ready systems. You will work with researchers and senior engineers across LLM pretraining, fine-tuning, reinforcement learning-based post-training, and evaluation.

The work emphasizes hands-on engineering, model quality, data strategies, and reliable implementation at scale. Key Responsibilities:

Apply RLVR, RLHF, and GRPO post-training techniques Build evaluation pipelines across tasks and domains Debug data, training, model, and precision issues Scale pipelines across LLM development stages Optimize training and inference workflows Requirements:

Bachelor’s or Master’s degree in a related field Four-plus years working with machine learning systems Strong Python programming skills Experience with PyTorch or comparable ML frameworks Understanding of transformers and machine learning fundamentals Apply machine learning, reinforcement learning, and systems expertise to advance Cerebras LLM training and deployment.

📌 Applied Machine Learning Research Scientist (Montreal)
🏢 Fdetimes
📍 Montreal