Machine Learning Engineer – Voice Conversion

Cantina

Machine Learning Engineer building state-of-the-art speech and voice-conversion systems for Cantina’s AI social platform. Owning models, data, evaluation, and production inference pipelines.

Posted 8/5/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSenior💰 $200,000 - $220,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and implementing large-scale speech models, with a strong focus on training methodologies, data management, and system optimization. Proficient in collaborating across teams to enhance speech technology and ensure responsible AI practices.

Highest-signal resume keywords

Large-Scale Audio ModelsDiffusion TransformersMulti-Node Distributed TrainingPyTorch ProficiencyVoice Cloning

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Large-Scale Audio ModelsDiffusion TransformersFlow-Matching TransformersAudio VAEsNeural Audio CodecsMulti-Node Distributed TrainingProduction-Quality CodePerformance ProfilingCUDAAdversarial Training

Tools & Technologies

FSDPDeepSpeedPyTorchCUDATriton

Industry Keywords

Speech TechnologyMachine LearningGenerative ModelsData CurationModel Evaluation

Tech Stack

Tools & technologies

Node.jsPyTorch

About the role

Key responsibilities & impact

Architect, implement, pre-train, fine-tune, and post-train/alignment large-scale speech models
Design, run, and analyze scientific experiments to advance understanding of models
Develop and improve development tooling to enhance team productivity
Contribute across the stack, from low-level optimizations to high-level model design
Define data requirements and collaborate on acquisition, curation, augmentation, labeling quality, and synthetic data strategies
Design automated objective and subjective evaluations, including listening tests, SV/WER/ASR-based metrics, robustness and bias checks, and red-team studies
Harden the training-to-evaluation-to-inference pipeline; profile latency, memory, and cost; meet production SLAs with monitoring and rollback
Contribute to safety and consent guardrails and misuse/abuse mitigation for responsible speech technology
Partner with research, data, infrastructure, and product teams to ship measurable improvements to speech systems

Requirements

What you’ll need

Exceptional research/development experience with large-scale audio models (>8B parameters, >500k hours of data)
Deep hands-on experience with diffusion and/or flow-matching transformers, including samplers, schedules, conditioning mechanisms, and distillation
Deep hands-on experience training audio VAEs, neural audio codecs, and vocoders, including latent/tokenizer design, reconstruction and perceptual objectives, and adversarial training
Strong experience with multi-node, multi-GPU distributed training using FSDP, DeepSpeed, or equivalent
Strong software engineering skills with a proven track record of building complex systems
Strong proficiency with PyTorch and performance work, including profiling and CUDA/Triton/C++ as needed
Experience writing reliable production-quality code
Experience shipping large-scale speech/audio or multimodal generative models to production
Background working with large-scale ML data and triangulating quality using subjective and objective signals
Experience with voice cloning, speech control/steerability, or expressive speech generation
Notable publications and/or open-source contributions in speech, audio, or machine learning

Benefits

Comp & perks

Competitive salary and generous company equity
Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina
42 days of paid time off, including 15 PTO days, 10 sick days, 15 company holidays, and 2 floating holidays
Generous parental leave & fertility support
401(k) retirement savings plan
Lifestyle spending account – $500/month to use however you’d like
Complimentary lunch and snacks for in-office employees
One Medical membership, and more!