Machine Learning Engineer - Voice Conversion

Responsibilities

• Architect, implement, pre-train, fine-tune, and post-train or align large-scale speech models, including GRPO and DPO approaches.
• Design, run, and analyze scientific experiments to advance model understanding.
• Develop and improve developer 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 training, evaluation, and inference pipelines; profile latency, memory, and cost; and meet production SLAs with monitoring and rollback.
• Contribute to safety and consent guardrails and misuse or abuse mitigation for speech technology.

Requirements

• Exceptional research or development experience with large-scale audio models exceeding 8B parameters and 500,000 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 technologies.
• Strong software engineering skills and experience building complex systems.
• Strong PyTorch and performance engineering skills, including profiling and use of CUDA, Triton, or C++ as needed.
• Experience shipping large-scale speech, audio, or multimodal generative models to production.
• Experience working with large-scale ML data and evaluating quality using subjective and objective signals.
• Experience with voice cloning, speech control or steerability, or expressive speech generation.
• Notable publications and/or open-source contributions in speech, audio, or machine learning.

Compensation and Benefits

• Annual base salary: $200,000-$220,000 (€170,000-€190,000).
• Competitive salary and generous company equity.
• Medical, dental, and vision insurance, with 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 and fertility support.
• 401(k) retirement savings plan.
• $500/month lifestyle spending account.
• Complimentary lunch and snacks for in-office employees.
• One Medical membership.