Machine Learning Engineer - Voice Conversion

Cantina Labs
United States
about 1 month ago
Apply on www.indeed.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$170,000.0 - $220,000.0
Working hours
Regular working hours
Job source

Tech stack

C++ (Programming Language) Profiling Codecs Nvidia CUDA Data Governance Machine Learning Node.Js Software Engineering Tokenization Pytorch Data Strategy Free and Open-Source Software
+2 more
Variational Autoencoders Stable Diffusion

Job description

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.

You will thrive in this role if you:

  • 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.

What You’ll Do:

  • 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.

Requirements

  • 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.

Benefits & conditions

Pulled from the full job description

  • Parental leave
  • Health insurance
  • Paid time off
  • Vision insurance
  • Dental insurance, 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.

Benefits for U.S.-based roles:

  • 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!

About the company

Cantina is a new social platform founded by Sean Parker with the most advanced AI character creator. Our bots are lifelike, social creatures that can interact wherever people are online-across voice, video, and text. Create yourself, imagine someone new, or choose from thousands of characters to share infinitely scalable, personalized content and seamless group chat.

If you’re excited about how AI can shape creativity and social interaction, come help us build what’s next.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.indeed.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:57 min

Leveraging large language models for voice coding context

Sami Ekblad Sami Ekblad · World Congress 2024

2:35 min

Preventing remote code execution in PyTorch models

Balázs Kiss · World Congress 2023

45 sec

Working securely with Node.js path application programming interfaces

Sonya Moisset · World Congress 2023

1:09 min

Integrating speech models using the Twilio real-time SDK

Marius Obert Marius Obert · Coffee With Developers

1:06 min

Compiling PyTorch environments for advanced time forecasting

Christoph Lohrmann Christoph Lohrmann +1 · World Congress 2026 Europe

3:55 min

Identifying underlying Node.js runtime vulnerabilities using fuzzing tools

Sonya Moisset · World Congress 2023

Videos

See all

Related articles

See all