Job Opportunities API

ABOUT RETELL AI Retell AI is using first principles to reimagine the call center with cutting-edge voice AI. Thousands of companies now utilize Retell’s AI voice agents to handle sales, support, and logistics calls that once required large teams of human agents. Backed by Y Combinator, Alt Capital, and other leading investors, we have scaled to $60M ARR with a team of 40 people, up from $5M at the start of 2025. Our vision for 2026 is to build a modern CX platform where entire contact centers are powered by AI. Instead of basic automation that needs constant human tuning, we’re creating intelligent AI “workers” that can act as frontline agents, QA analysts, and managers, continuously executing, monitoring, and improving customer interactions. We’re growing quickly and looking for ambitious builders who want to tackle hard technical problems, move fast, and have real impact at one of the fastest-growing voice AI startups. Let’s build the future together. - We’re a top 50 AI app in a16z list: https://tinyurl.com/5853dt2x - #4 on Brex's Fast-Growing Software Vendors of 2025: https://www.brex.com/journal/brex-benchmark-december-2025 - We're also one of the top ranking startups on: https://leanaileaderboard.com/ - Enterprise tech 30: https://www.wing.vc/et30/overview ABOUT THE ROLE This is a research-driven, high-impact role for ML researchers who want to push the boundaries of real-time AI. As a Founding Machine Learning Research Engineer at Retell, you’ll focus on advancing model capabilities for human-like voice agents operating in complex, real-world environments. You’ll explore new approaches across LLMs and audio models, design novel evaluation methods, and prototype systems that improve reasoning, latency, and conversational quality. Your work will directly influence production systems, bridging cutting-edge research with real-world deployment. If you’re excited about solving open-ended ML problems, experimenting rapidly, and shaping how voice AI systems think and perform, this is a unique opportunity to do so at scale. KEY RESPONSIBILITIES - Research & Experimentation – Explore and develop new techniques across LLMs and audio models to improve reasoning, latency, and conversational quality in real-time systems. - Model Training – Rapidly build and iterate on models and pipelines, turning research ideas into working prototypes. Innovate on paradigms, training methods, and inference. - Evaluation & Benchmarking – Design novel evaluation frameworks, datasets, and metrics to measure performance on complex, real-world voice tasks. - Bridge Research to Production – Collaborate closely with engineering to translate research insights into deployable systems. - Human Feedback Loops – Develop methods to incorporate human evaluation into model improvement, especially for subjective conversational quality. - Advance the Frontier – Stay at the cutting edge of ML research and bring new ideas into Retell’s product and infrastructure. REQUIRED - Strong ML Research Background – You've worked on advanced ML problems (like LLM pre-training and post-training, transcription model training, TTS, or multimodal systems), either in industry or academia. - Deep Technical Foundation – Comfortable with PyTorch, model architectures, and the math behind modern machine learning. - Top Academic Background – Master's degree in CS, ML, AI or related field required; PhD preferred. Equivalent research-level engineering experience also considered.   YOU MIGHT THRIVE IF YOU - Published or Awarded – First/co-author publications at top-tier venues (NeurIPS, ICML, ICLR, ACL, Interspeech, etc.) or notable competition awards are a strong plus. - Experimental Mindset – You enjoy exploring open-ended problems and iterating quickly on ideas. - Bridge Theory & Practice – You can translate research into systems that work in real-world environments. - Startup-Ready –