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.

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