Teams at AssemblyAI

Build and maintain finance data pipelines, warehouse models, dashboards, and automations for unit economics, technology budgeting, burn, runway, margins, deal desk, and sales compensation. Develop internal tools and LLM-based agents that help non-engineers access trusted financial data. Partner with finance, sales, and engineering leadership to reconcile discrepancies and improve revenue, cost, billing, payroll, cloud-spend, and accounting workflows.

Develop and optimize large-scale deep learning training, data processing, and production inference systems. Maintain JAX and TPU training infrastructure, improve data quality and evaluation, translate research prototypes into production, optimize speech and language model inference, and resolve performance bottlenecks from kernels through system architecture. Collaborate across research, infrastructure, and production engineering while measuring impact and improving experimental velocity.

Build and scale production inference systems and customer-facing APIs for AssemblyAI’s voice AI models. Responsibilities include productionizing research prototypes, improving latency and reliability, supporting high-volume inference traffic, developing backend services and SDKs, and collaborating with researchers, applied engineers, customers, and product teams.