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Stealth Startup in Redwood City is looking for a Founding Senior Machine Learning Engineer to develop AI voice agents capable of managing millions of real-time conversations. The role involves fine-tuning large models, deploying them to production, and shaping the ML strategy.
This position offers a base salary between $225,000 and $325,000, equity options, and generous benefits including medical insurance and a daily DoorDash credit. Candidates who thrive in a fast-paced, startup environment are encouraged to apply.
The Company 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 Company’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.
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 The Company, 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.