Senior Machine Learning Engineer, Voice AI

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

$200K-$260K From the posting source checked Jun 20, 2026

401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

97% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Company stage

Growth-stage From the posting source checked Jun 20, 2026

Equity

Offered From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Senior Machine Learning Engineer, Voice AI San Francisco About the Role Together AI is building the best inference infrastructure for voice applications. Our Voice AI platform powers production-grade, real-time voice agents and applications - serving speech-to-text and text-to-speech models with best-in-class latency and reliability. We're looking for a Senior ML Engineer to drive the model serving layer for voice workloads. You'll work hands-on with inference engines like TRT-LLM and SGLang to optimize how we serve models like Whisper, Parakeet, Orpheus, and Kokoro - pushing latency and throughput to the frontier. You'll profile GPU utilization, design batching strategies for streaming audio, and ensure new model architectures can go from research to production quickly. This is a foundational hire on a small, high-impact team. Voice inference has unique challenges - streaming audio, tokenization, real-time latency budgets - that require dedicated ML engineering focus. You'll shape how Together serves voice models as the industry moves from pipeline architectures (ASR → LLM → TTS) toward end-to-end speech-to-speech. - Own the model serving stack that powers Together's voice platform across STT, TTS, and speech-to-speech. - Work directly with state-of-the-art accelerators (H100s, H200s, B200s) to optimize voice model inference. - Collaborate with model partners (Cartesia, Deepgram, Rime, and others) to bring their models to production on Together's infrastructure. - Build quality evaluation frameworks that guide model selection for customers and inform the roadmap. - Join a small, early-stage team with outsized impact on a fast-growing product area. Responsibilities - Optimize inference performance for voice models (STT,

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