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Cantina

Subscription-based platform for AI-driven social gaming

Machine Learning Engineer - Text-to-Speech

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeRemote

About the Job

Requirements

  • Exceptional research and development experience with large-scale audio models exceeding 3 billion parameters and over 500,000 hours of data.
  • Exceptional understanding and hands-on experience with transformer architectures, diffusion models including distillation and streaming, and/or audio language modeling.
  • Strong experience with multi-node and multi-GPU distributed model training.
  • Strong software engineering skills and a proven track record of building complex systems.
  • Strong experience with PyTorch and performance work, including profiling, CUDA, Triton, or C++ as needed, and writing reliable production-quality code.
  • Experience shipping large-scale speech or audio models to production.
  • Background working with large-scale machine-learning data.
  • Ability to iterate on data and assess quality using subjective and objective signals.
  • Notable publications and/or open-source contributions in speech, audio, or machine learning.
  • Experience with voice cloning, speech control, and voice generation.

Responsibilities

  • Architect, implement, pre-train, fine-tune, and post-train or align large-scale speech models, including methods such as GRPO and DPO.
  • Independently lead small research projects and collaborate on larger team initiatives.
  • Design, run, and analyze scientific experiments to advance understanding of the models.
  • 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 data 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, evaluation, and inference pipeline; profile latency, memory, and cost; and meet production service-level agreements with robust monitoring and rollback.
  • Partner with infrastructure teams to run distributed training and inference on cloud fleets and productionize models with reliability and observability.
  • Contribute to safety and consent guardrails and to misuse and abuse mitigation for responsible speech technology.

Desired Qualifications

  • Experience shipping large-scale speech or audio models, including text-to-speech, voice conversion, or automatic speech recognition, to production.
  • Experience working on large-scale machine-learning systems.
  • Experience with audio language modeling and transformer architectures.
  • Experience with voice cloning, speech control, and voice generation.
  • Background in processing large-scale machine-learning data.
  • Publications or notable open-source contributions in speech, audio, or machine learning.

About the Company

Cantina

Subscription-based platform for AI-driven social gaming

Cantina is a private, invitation-only platform that blends social gaming with AI-driven bots. Members join a 24/7 virtual club where they can chat with bots, play games, and create AI art under a monthly subscription. Bots have distinct personalities and adapt to user inputs, delivering personalized interactions in a shared space. It differentiates itself by offering a private, customizable, AI-driven social experience for tech-savvy gamers, with a goal to grow a steady subscription-based service and attract brand partnerships.

Company size
51-200
Company stage
Series B
Total funding
$33.3M
Headquarters
San Francisco, CA
Founded
2014

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