Senior Machine Learning Engineer

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 Leaderboard Backed by Y Combinator ABOUT THE ROLE 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 hands-on, high-ownership role for ML engineers who want to build production models that actually ship, and perform under real-world constraints. As a Founding Senior Machine Learning Engineer at Retell, you’ll work across the ML stack to power human‑like voice agents that handle millions of real-time phone conversations. You’ll fine‑tune large language models and audio models, evaluate them with rigorous benchmarks (and human feedback), and deploy them into latency‑sensitive, high‑traffic systems. You’ll own model performance end‑to‑end—from training pipelines to post‑deployment monitoring—and shape our ML strategy alongside the founding team. If you’re excited by hard technical challenges, fast iteration, and the opportunity to define how voice AI works at scale, this role is a rare chance to do it from the ground up.

KEY RESPONSIBILITIES

Train & Tune Models – Fine‑tune LLMs and audio models to maximize speed, accuracy, and production‑readiness—pushing the frontier of real‑time AI voice experiences. Benchmark & Evaluate – Build datasets, define rigorous metrics, and measure model performance across high‑impact voice AI tasks to guide development. Deploy to Production – Work closely with engineering to ship models, monitor them in the wild, and ensure they stay fast, reliable, and accurate at scale. Run Human Evaluations – Build scalable pipelines to collect structured human feedback, benchmark subjective quality, and inform model iterations. Level Up Infrastructure – Design and maintain the ML infrastructure needed for fast experimentation, robust training, and continuous deployment.

YOU MIGHT THRIVE IF YOU

ML Engineer with Real-World Experience – You’ve trained and shipped models in production. Bonus if you’ve worked with LLMs or audio models. Fluent in Modern ML Stack – You know your way around Python, PyTorch, and today’s ML tools—from training pipelines to evaluation benchmarks. Execution‑Oriented – You move fast, take ownership, and focus on solving real problems over perfect ones. Startup‑Ready – You’re adaptable, resilient, and energized by ambiguity and fast‑changing priorities. Clear Communicator & Team Player – You collaborate well across functions and push decisions forward.

JOB DETAILS

Cash: $225,000 - $325,000 base salary Equity: Offers Equity Location: Redwood City, CA, US 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 breakfast, lunch, dinner, and snacks
• 200/month wellness reimbursement (gym, fitness classes, etc.)
• 300/month commuter reimbursement (gas, Caltrain, etc.)
• 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) to attract high performers. High Ownership: Small teams, >$1M revenue/employee, and significant equity. Performance‑Based: Offers tied to interview performance, not experience or 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) : MLE coding Technical Interview (45 min) : ML questions deepdive Onsite/Virtual Interviews (3 hrs) : Hosted in our office if located in the Bay Area or virtual, with three rounds: ML System Design: A non‑coding interview focused on whiteboarding and high‑level system architecture. ML Question Deep Dive: In‑depth discussion exploring your approach to a machine learning problem. Backend + AI Practical: A hands‑on coding interview combining backend development with AI integration.

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