Model Distillation Engineer

Hark is an artificial intelligence company focused on creating advanced, personalized intelligence systems. They are seeking a Model Distillation Engineer to compress large audio and multimodal models into student models that fit the constraints of their hardware, while managing distillation, quantization, and architecture-aware compression processes.

Responsibilities:

• Design and execute distillation strategies (response, feature, and self-distillation) to compress teacher models into deployable students
• Apply quantization (PTQ and QAT), pruning, and architecture search to hit per-product size, latency, and power budgets
• Build a reusable distillation and compression toolchain that the broader audio ML team can adopt across model families
• Partner with the broader audio ML team on training pipelines and with the runtime team on deployment targets
• Define accuracy retention and resource KPIs per product and track them through the release cycle
• Profile compressed models on target hardware and iterate with DSP and runtime engineers on bottlenecks