Software Engineer, Machine Learning

Summary

Join AssemblyAI, a leading Speech AI company, as a Machine Learning Engineer to accelerate our AI research-to-production pipeline. You will design and implement tooling for researchers to deploy and evaluate new models, build and maintain high-performance inference pipelines, optimize infrastructure, develop user-facing APIs, and implement observability solutions. This cross-functional role requires collaboration with research and engineering teams. The ideal candidate possesses strong backend engineering experience with Python, distributed systems, and containerization, preferably on AWS. AssemblyAI offers a competitive salary and benefits package.

Requirements

• Strong backend engineering experience with Python
• Experience building and operating distributed, containerized applications, preferably on AWS
• Proficiency implementing observability solutions (monitoring, logging, alerting) for production systems
• Ability to design and implement resilient, scalable architectures

Responsibilities

• Design and implement tooling that enables researchers to quickly deploy and evaluate new models in production
• Build and maintain high-performance, cost-efficient inference pipelines in production
• Optimize infrastructure for both iteration speed and production reliability
• Develop and maintain user-facing APIs that interact with our ML systems
• Implement comprehensive observability solutions to monitor model performance and system health
• Troubleshoot complex production issues across distributed systems
• Continuously improve our MLOps practices to reduce friction between research and production

Preferred Qualifications

• MLOps experience, including familiarity with PyTorch and Kubernetes
• Experience working in startup environments demonstrating ownership, decisiveness, and rapid iteration
• Experience collaborating with remote, globally distributed teams
• Comfort working across the entire ML lifecycle from model serving to API development
• Experience in audio-related domains (ASR, TTS, or other domains involving audio processing)
• Experience with other cloud providers
• Familiarity with Ray.io, Bazel, and monorepos
• Experience with alternative ML inference frameworks beyond PyTorch
• Experience optimizing for low-latency, real-time inference

Benefits

Salary range: $157,500-$175,000