Research Scientist - LLM

ABOUT RETELL AI

Retell AI is using first-principles thinking to reimagine the call center with cutting-edge voice AI. Thousands of companies now use 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've scaled to $80M in ARR with a team of 50, up from $5M at the start of 2025, and are now valued at over $1.5B.

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 act as frontline agents, QA analysts, and managers, continuously executing, monitoring, and improving every customer interaction.

We're growing fast and looking for ambitious builders who want to tackle hard technical problems, move quickly, and have a real impact on one of the fastest-growing voice AI companies in the world.

Let's build the future together.

Recent recognition:

• No. 1 Best Places to Work in the Bay Area, San Francisco Business Times 2026

• Top 50 AI Apps, a16z (2025)

• #3 Fastest-Growing Software Company, G2 Best Software Awards 2026

• Best Agentic AI Software, G2 Best Software Awards 2026

• #4 Fastest-Growing Software Vendor, Brex Benchmark 2025

• Enterprise Tech 30 Class of 2026, Nasdaq & Wing VC

• Top-Ranked Startup, Lean AI Leader board

• Backed by Y Combinator

Retell AI transforms customer experience with voice AI for enterprises, including customers like CVS/Aetna, American Airlines, Lenovo, and Grab. We have more customer stories than we can tell!

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.

• 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.

• 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.

• 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.

• Start…