TL;DR

Staff Software Engineer, Infrastructure (ML and Real-Time Speech): Building and scaling backend platforms for advanced multi-language automatic speech recognition and real-time speaker identification systems with an accent on designing fault-tolerant infrastructure and collaborating with machine learning teams. Focus on solving complex distributed-systems challenges and improving system performance for large-scale speech data.

Location: Mountain View, CA

Company

%hirify_global% is the world’s leading tool for meeting transcription, summarization, and collaboration, using AI to generate real-time automated meeting notes and insights.

What you will do

Design, build, and operate backend services for real-time ASR and speaker identification.
Architect scalable infrastructure to support low-latency ML workflows.
Collaborate with ML teams for model deployment and monitoring.
Improve system observability and performance for speech data ingestion.
Contribute to platform architecture evolution, including microservices and API integrations.
Streamline developer experience and CI/CD pipelines for ML services.

Requirements

10+ years of experience in scalable backend systems and distributed infrastructure.
Fluency in Python (C++ is a bonus).
Deep understanding of data structures, algorithms, and operating systems.
Experience with SQL & NoSQL databases and queuing systems.
Familiarity with ML infrastructure or eagerness to learn.
Ability to collaborate with ML engineers and product teams.