ABOUT RETELL AI
Retell AI is using the first principles to reimagine the call center with cutting edge voice AI.
Since launching 18 months ago, 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 $36M ARR with a team of 20 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.
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 Prototyping – Rapidly build and iterate on experimental models and pipelines, turning research ideas into working prototypes.
- 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.
YOU MIGHT THRIVE IF YOU
- Strong ML Research Background – You've worked on advanced ML problems (for example: LLM pre-training and post training, transcription model training, text to speech model training, or multimodal systems), either in industry or academia.
- Deep Technical Foundation – Comfortable with PyTorch, model architectures, and the math behind modern machine learning.
- Experimental Mindset – You enjoy exploring open-ended problems and iterating quickly on ideas.
- Bridging Theory & Practice – You can translate research into systems that work in real-world environments.
- Startup-Ready – You thrive in fast-paced environments with high ownership and ambiguity.
- Collaborative & Clear Communicator – You can explain complex ideas and work cross-functionally to drive impact.
JOB DETAILS
- Cash: $225,000 - $400,000 base salary
- Equity: Offers Equity
- Location: Redwood City, CA, US (100% Relocation Provided)
- US Visas: Retell AI is open to sponsoring work authorization for qualified candidates, including H1B/H-1B, TN, L-1, E-3, F-1 (OPT/CPT), and O-1 visas.
OTHER BENEFITS
- 100% coverage for medical, dental, and vision insurance
- $70/day DoorDash credit for unlimited meals and snacks
- $200/month wellness reimbursement
- $300/month commuter reimbursement
- $75/month phone bill reimbursement
- $50/month internet reimbursement
COMPENSATION PHILOSOPHY
- Best Offer Upfront: Choose from three cash-equity balance options, no negotiation needed
- Top 1% Talent: Above-market pay (top 5 percentile)
- High Ownership: Small teams, >$1M revenue/employee, significant equity
- Performance-Based: Offers tied to interview performance, not past salaries
INTERVIEW PROCESS
- Talent Screen (15min): chat with our recruiter to get a better sense of the role, the team, and what it's like to work here.
- Technical Interview (45 min): LLM theory specific coding Interview (PyTorch)
- Technical Interview (45 min): Live Practical Systems Design and Coding Interview.
- Onsite/Virtual Interviews (3 hrs): Hosted in our office if located in the Bay Area or virtual, with three rounds:
- ML System Design
- ML Question Deep Dive
- Backend + AI Practical