---
title: 'Machine Learning Scientist at Rime Labs'
canonical: 'https://feeny.ai/job/machine-learning-scientist-rime-labs-united-states-r8cqrr7exaes'
type: 'job'
last_seen: '2026-09-06'
---

# Machine Learning Scientist at Rime Labs

- **Company:** Rime Labs
- **Location:** United States
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-05-15
- **Last confirmed live:** 2026-09-06
- **Apply:** https://jobs.ashbyhq.com/rime/b76243da-3ce0-463e-9f29-2b6d1b78666e

## Job description

## MACHINE LEARNING SCIENTIST

Rime builds voice AI for enterprises running customer experiences at scale. Our text-to-speech models are purpose-built for high-volume conversational deployments, engineered for the pronunciation accuracy, latency, and deployment flexibility that production environments actually demand.

We started from a different premise than the rest of the field: voice AI isn't bottlenecked by model architecture. It's bottlenecked by data. So before we trained a single model, we built our own corpus: full-duplex, studio-quality conversational speech, recorded and annotated by PhD linguists. That's our moat. It's also why enterprises pick Rime when pilots need to convert into production.

We're backed by top-tier investors including Unusual Ventures, and we've built a team at the intersection of product, research, and craft. Building voice models is an art. We intend to master it.

## ROLE OVERVIEW

We're hiring a Machine Learning Scientist to push the frontier of speech synthesis and speech understanding at Rime.

## What You'll Own

- Design, train, and evaluate speech synthesis models, autoregressive and non-autoregressive.
- Drive research on full-duplex and half-duplex multi-modal architectures, including unified S2S systems.
- Choose and iterate on speech representations: neural codecs, semantic tokens, mel features, continuous latents.
- Build rigorous evaluation, objective and perceptual. Hold the bar on quality and prosodic control.
- Collaborate with our linguists on TTS frontend behavior so modeling and frontend choices reinforce each other.

## WHAT WE'RE LOOKING FOR

- Deep familiarity with the speech synthesis literature, contemporary and historical — Tacotron, FastSpeech, VITS, VALL-E, the codec-LM lineage. Opinions on what worked and why.
- Hands-on training with neural codecs (EnCodec, DAC, Mimi, etc.) and multiple representation choices.
- Experience with full- or half-duplex multi-modal modeling (Moshi, LLaMA-Omni, streaming S2S).
- Strong attention to detail on data quality. You notice when an annotation pipeline is silently degrading or when an eval set has leakage.
- Willing to roll up your sleeves on unglamorous data and training work — paired with the agency to build pipelines so the team isn't stuck doing it by hand.
- Working knowledge of TTS frontend (G2P, normalization, prosody) and experience working with linguists.
- Strong PyTorch fundamentals. Comfortable with training loops, distributed training, model internals.
- PhD or equivalent research experience in speech, audio, ML, or computational linguistics or a track record that makes the credential irrelevant.

## Nice to have

- Multilingual TTS experience.
- Background in prosody or paralinguistics.
- Published work in speech, audio, or core ML venues.
- Experience taking research models to production: quantization, distillation, streaming inference.

## WHY JOIN RIME

- Category-defining voice AI infrastructure, not incremental research deltas.
- Direct collaboration with founders, including a CEO with a Stanford computational linguistics PhD.
- Real impact on company trajectory.
- Meaningful equity upside.
- High ownership, high standards, low bureaucracy.

## What We Offer

- Competitive base + meaningful early-stage equity
- Remote-friendly
- Visa sponsorship available
- Access to a proprietary, full-duplex, studio-quality conversational speech corpus
- Compute and tooling to do the work
- Direct influence on the future of voice AI

At Rime, we...

- Are outliers
- Cut through the hype to focus on the craft
- Move fast with agency and freedom
- Maintain a growth mindset, finding joy in the struggle
- Do the right things, knowing that it'll lead to making money

If that sounds like you too, you'll be a great fit for Rime!

## About Rime Labs

## Company Overview
- **One-liner**: Rime Labs develops enterprise-grade, ultra-realistic text-to-speech AI voice models designed for production contact center, healthcare, and financial applications.
- **Entity Type**: Private (venture-backed, Seed stage)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2022
- **Founders**: Lily Clifford (CEO), Brooke Larson (PhD Linguist, ex-Amazon Alexa), Ares Geovanos (COO)

## Core Business
- **Primary Industry**: Artificial Intelligence / Voice AI (Text-to-Speech), Enterprise Software
- **Target Customers**: B2B, Enterprise (contact centers, healthcare providers, financial institutions, telecom)
- **Mission Statement**: "Make voice AI sound and feel human."

## Products & Services
- **[Coda](https://rime.ai/)**: Flagship TTS model blending human-quality voice with enterprise-grade speed and concurrency. Optimized for production deployments.
- **[Arcana](https://rime.ai/)**: Most expressive and human-like TTS model with 300+ voices, bilingual/multilingual support, and instant code-switching (English, Spanish, Spanglish). Designed for warm, emotionally resonant conversations.
- **[Mist](https://rime.ai/)**: High-speed enterprise TTS with sub-200 ms cloud latency and <100 ms on-prem. Supports high-volume streaming and extensive customization.
- **[SpeechQA](https://rime.ai/)**: Tool to flag low-confidence words before deployment, enabling proactive pronunciation fixes.

## Market Standing
- **Valuation**: Conflicting reports – PitchBook indicates a post-money valuation of ~$9.6M as of May 2025; LinkedIn reports total funding of $8.6M. Not publicly disclosed.
- **Key Metric (Private)**: Total Funding – $8.6M across two seed rounds (June 2023: $3.1M; June 2025: $5.5M). PitchBook lists a $6.5M seed round in May 2025 with 22 investors.
- **Notable Investors**: Unusual Ventures (lead), Cadenza Capital, Founders You Should Know, and angel investors.
- **Growth Signals**: 33 employees (+245.5% YoY); operates in 9 countries; powers tens of millions of conversations monthly across industries including healthcare and food service.

## Competitive Advantages
- **Proprietary Dataset**: One of the largest collections of expressive, multilingual conversational speech, captured in-studio and across diverse U.S. locations.
- **Deep Linguistic Expertise**: Founders include a Stanford NLP PhD dropout and a PhD linguist from Amazon Alexa; models trained on real-world speech patterns (interruptions, laughter, disfluencies).
- **Enterprise-Ready Compliance**: SOC 2 Type II and HIPAA compliant; deployable on-prem, in VPC, or via cloud API.
- **Pronunciation Control**: Fine-grained tools to fix pronunciations in minutes without retraining; built-in handling of brand names, drug names, and numbers.
- **Low Latency at Scale**: Sub-200 ms cloud latency; <100 ms on-prem; designed for production loads, not just demos.

## Strategic Focus
- Deepening enterprise adoption in regulated industries (healthcare, finance, telecom).
- Expanding multilingual and code-switching capabilities (English/Spanish/Spanglish).
- Scaling the engineering and go-to-market teams to meet growing demand (VP of Engineering, Founding Account Executive roles open).

## Why Work Here
- **Culture**: Small, passionate, lean team based in San Francisco. Emphasis on pushing boundaries in voice AI and creating technology that connects with real people.
- **Work Environment**: Likely hybrid/office in San Francisco (HQ); on-site recording studio. Notable perks: direct impact on product direction, access to cutting-edge ML and linguistics research.
- **Open Roles** (7 as of mid-2026): Solutions Engineer, Solutions Engineering Manager, Developer Advocate, Founding Account Executive, VP of Engineering, Revenue Operations, Product Marketing Manager.
- **Engineering Culture**: Strong focus on ML, low-latency systems, and production reliability. Team includes engineers from Meta, Stanford, and speech startups.

## Sources
1. [rime.ai - Homepage](https://rime.ai/)
2. [rime.ai - Company Page](https://rime.ai/company)
3. [LinkedIn - Rime AI](https://www.linkedin.com/company/rime-ai)
4. [PitchBook - Rime Labs Profile](https://pitchbook.com/profiles/company/528897-34)
5. [Ashby - Rime Labs Careers](https://jobs.ashbyhq.com/rime)

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