Applied AI Scientist, Small Language Model and AI Training

Lead research and development of novel training methodologies and architectures for small and efficient language models, design, implement, and evaluate model training experiments to improve performance, robustness, and generalization of language models, collaborate closely with research scientists and engineers on scalable training pipelines and model deployment strategies, develop techniques for model compression, fine-tuning, and domain adaptation to optimize models for real-world applications, ensure AI safety, fairness, and alignment principles are integrated into model training processes and evaluated rigorously, mentor and support cross-functional teams on applied machine learning methods and best practices, evaluate and integrate new tools, frameworks, and datasets to accelerate AI training workflows, partner with product teams to translate model capabilities into actionable features aligned with user needs and ethical standards.

Candidates will join an innovative team pushing engineering boundaries. Depending on the domains associated with this job, you will be expected to design clean APIs, write automated test cases, and participate in peer code reviews. We value developers who focus on performance optimization, fast load times, and simple, maintainable architectures.