Machine Learning Engineer — Distillation

Responsibilities:

• Design and implement advanced knowledge distillation pipelines, including teacher-student approaches, self-distillation, and multi-teacher architectures.
• Distill large foundation models into smaller, faster, and more efficient models optimized for production inference.
• Run large-scale machine learning experiments to evaluate model quality, latency, efficiency, and cost tradeoffs.

Requirements:

• Strong background in machine learning, deep learning, and neural network architectures.
• Hands-on experience implementing model distillation techniques for large language models or other neural networks.
• Solid understanding of training dynamics, optimization methods, loss functions, and model evaluation.

Benefits:

• Competitive compensation package with meaningful equity opportunities.
• Opportunity to work on core machine learning systems that directly impact product performance and efficiency.
• Remote-friendly work environment with an async-first culture.