Machine Learning Engineer - Voice Conversion

We're looking for a Research / ML Engineer to join our Speech Team to build state-of-the-art speech systems end-to-end-from data specs through production inference. You'll drive the model ↔ data ↔ eval flywheel for VC and adjacent tasks (controllable TTS, voice design and more), partnering closely with research, data, and infra to ship fast, reliable, and cost-aware models.

In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems.

- See research and engineering as two sides of the same coin and enjoy owning work end-to-end.

- Are results-oriented, flexible, and willing to pick up whatever moves the needle.

- Like collaborating closely with infra, data, and product to ship measurable improvements.

- Enjoy designing experiments, listening tests, and metrics that correlate with user-perceived quality.

- Eager to learn every-day, find and solve unique large-scale problems.

- Model Building: Architect, implement, pre-train, fine-tune, and post-train/alignment (e.g., GRPO/DPO) for large-scale speech models.

- Experimental Design: Design, run, and analyze scientific experiments to advance our understanding of the models.

- Tool Development: Develop and improve dev tooling to enhance team productivity.

- Full-Stack Contribution: Contribute to the entire stack, from low-level optimizations to high-level model design.

- Data Ownership: Define data requirements and collaborate on acquisition, curation, augmentation, labeling quality, and synthetic data strategies.

- Rigorous Evaluation: Design automated objective/subjective evaluations-listening tests, SV/WER/ASR-based metrics, robustness & bias checks, and red-team studies.

- Pipeline Delivery: Harden the training → evaluation → inference pipeline; profile latency, memory, and cost; and meet production SLAs with robust monitoring and rollback.

- Safety &

Responsibility: Contribute to safety/consent guardrails and to misuse/abuse mitigation for responsible speech technology.

- 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 practical knowledge of samplers, schedules, conditioning mechanisms, and distillation.

- Deep hands-on experience training audio VAEs, neural audio codecs, and vocoders latent/tokenizer design, reconstruction and perceptual objectives, adversarial training.

- Strong experience with multi-node, multi-GPU distributed training (FSDP/DeepSpeed or equivalent).

- Strong software engineering skills with a proven track record of building complex systems.

- Strong with PyTorch and performance work (profiling, CUDA/Triton/C++ as needed) and writing reliable production-quality code.

- Shipped large-scale speech/audio or multimodal generative models to production.

- Background in working with large-scale ML data, and the ability to iterate on data and triangulate quality using both 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/ML.

The anticipated annual base salary range for this role is between $200,000-$220,000 (€170,000-€190,000). When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.

- 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

- 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!