Machine Learning Scientist

Rime; San Francisco (CA); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Remote-friendly

Visa sponsorship available

Equity upside

Access to a studio-quality corpus

Job summary

Rime is building voice AI for enterprises with scalable customer experiences. We seek a Machine Learning Scientist to push the frontier of speech synthesis and understanding, training and evaluating advanced models and collaborating with linguists to ensure frontend choices reinforce modeling decisions.

The role offers remote-friendly work, visa sponsorship, and meaningful equity upside, with ownership and high standards to move fast and impact product trajectory.

Qualifications

• PhD or equivalent research experience in speech, audio, ML, or computational linguistics.
• Strong PyTorch fundamentals; training loops and distributed training.
• Hands-on training with neural codecs and multiple representation choices.
• Experience with full- or half-duplex multi-modal modeling.

Responsibilities

• 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 metrics; ensure quality and prosodic control.
• Collaborate with linguists on TTS frontend behavior so modeling and frontend choices reinforce each other.

Education

PhD or equivalent research experience in speech, audio, ML, or computational linguistics

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!