Voice AI Research Engineer

About UsInvorto is our Voice AI product, bringing intelligent voice agents to real-world customer and operational use cases. Our voice pipeline is built in Python, running an STT → LLM → TTS architecture on top of the Pipecat framework.This is a chance to work on hard problems in voice AI — latency, accuracy, naturalness, and reliability — building zero-to-one, owning your area end-to-end, and shipping to production at scale.Note: This is a customer-facing role, and strong communication skills are essential.About the RoleWe're looking for a Voice AI Research Engineer to join the Invorto team and help build and continuously improve the voice AI systems that power our intelligent voice agents. This role is focused on the specialized craft of voice AI — designing evaluation and automation frameworks that ensure our STT, LLM, and TTS pipeline performs reliably in real-world, production conditions. What You'll DoDesign and build automated testing and quality frameworks for our STT → LLM → TTS voice pipeline, built on PipecatEvaluate and benchmark STT, LLM, and TTS/ASR components on accuracy, latency, naturalness, and robustness across accents, languages, and real-world audio conditionsWork hands-on with STT, TTS, and ASR models — fine-tuning, evaluating, and improving them for production use casesIdentify failure modes and edge cases across the pipeline (background noise, accents, interruptions, turn-taking, latency, pipeline-stage handoffs) and build systems to catch them before productionCollaborate closely with engineering to integrate quality checks and automation into the voice agent development lifecycle within the Pipecat-based architectureResearch and stay current with advances in voice AI, and bring in new techniques, models, and tools to improve pipeline performanceWork directly with customers to understand real-world voice use cases and translate them into evaluation criteria and quality benchmarksPartner with product and engineering to define what "production-grade quality" means for voice agents and drive the team toward it What We're Looking For4–6 years of experience, with a specialization in voice AI systems and automated quality evaluationHands-on experience with STT (Speech-to-Text), TTS (Text-to-Speech), and ASR (Automatic Speech Recognition) modelsExperience designing and building automated testing/evaluation frameworks for voice or speech systemsStrong understanding of what drives voice AI quality — accuracy, latency, naturalness, and robustness to real-world variabilityStrong programming skills in Python; familiarity with Pipecat or similar voice pipeline/orchestration frameworks is a plusUnderstanding of STT → LLM → TTS pipeline architectures and the trade-offs involved at each stageResearch mindset — comfortable exploring new models, techniques, and tools and translating them into practical improvementsExcellent communication skills — this is a customer-facing role, and you'll regularly engage directly with customers to understand needs and validate quality expectations