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Posted Apr 14Research Scientist - Audio
at Retell AI
On-site
Responsibilities
- Innovate on paradigms, training methods, and inference.
Requirements
- 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.
- 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.
- 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
- - 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.
- 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.