What You’ll Do

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.

About You

Have demonstrated experience in applied research or engineering roles focused on training language models, ideally small or efficient models.
Strong programming skills in Python and familiarity with machine learning frameworks such as PyTorch, TensorFlow, or JAX.
Deep understanding of language model architectures, training techniques, and optimization strategies.
Experience with distributed training, data pipeline design, and scalable AI infrastructure.
Passion for AI safety, interpretability, and delivering user-centered AI technology.
Excellent communication skills with proven ability to collaborate across research, engineering, and product teams.

Prior experience working with large and small language models in production or research settings.
Background in reinforcement learning, prompt engineering, or transfer learning techniques.
Experience with developer tools, APIs, or frameworks related to AI model integration and delivery.
Knowledge of AI alignment, fairness, and ethical AI training methodologies.