Software Engineer, Telnyx

• We’re looking for a Python Engineer with a passion for AI and a knack for building high-performance, low-latency systems
• 3+ years of professional software development experience in Python
• Strong grasp of async Python frameworks (e.g. FastAPI, Starlette)
• Experience with web app development and microservice architecture
• Comfortable working with relational databases at scale
• Familiar with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
• Experience deploying and maintaining ML models in production environments
• Understanding of scalable, distributed systems
• Excellent communication skills and the ability to work cross-functionally

Desirable

• You’ll work in a fast-paced environment within our AI-native team, helping power Telnyx AI, our cutting-edge platform delivering intelligent communication tools through speech, embeddings, and scalable inference infrastructure
• This is an exciting opportunity to help shape TelnyxAI from the ground up
• You’ll collaborate with the wider team here to integrate open-source LLM tools and build scalable microservices that make AI accessible, reliable, and real-time
• Our Python team builds highly available, low-latency microservices using bleeding-edge technologies
• This role focuses on developing our AI applications and infrastructure, from model deployment to product-facing APIs, with a particular emphasis on text and voice interfaces
• Designing developer-friendly APIs to interact with inference and embeddings services
• Building internal tools and services to streamline AI workflows across teams
• Creating integrations between our Storage and Voice APIs and LLM-based systems
• Applying distributed computing tools like Ray to deploy, scale, and optimize ML models
• Keeping TelnyxAI at the forefront of modern AI/ML trends and best practices
• Build, test, and deploy scalable Python microservices for AI inference and text/voice processing
• Develop APIs and internal tools that make AI easy to use across our product ecosystem
• Optimize performance and latency in production environments
• Continuously evaluate and integrate emerging AI technologies and LLM frameworks
• Collaborate with cross-functional teams (Product, Infra, ML) to bring features from ideation to production
• Troubleshoot, debug, and monitor critical systems in production
• Participate in code reviews and uphold high-quality engineering standards