Applied Machine Learning Research Scientist

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 modern 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.