Machine Learning Engineer, TTS

Devconnectplatform; United States; Remote; USD 150.000 - 210.000; Vollzeit

Benefits dieser Stelle

Medical/Dental/Vision insurance

Equity opportunity

Paid time off 42 days

401(k)

Zusammenfassung

Cantina, a social platform building AI-driven characters, is hiring a Senior ML Engineer for its Speech Team. You will drive end-to-end development of state-of-the-art speech systems, from data specs to production inference, focusing on safe, steerable AI and scalable pipelines.

Join a fast-moving team as you architect and optimize large-scale audio models, lead experiments, and collaborate with research, data, and infra to ship reliable solutions with strong performance and cost awareness.

Qualifikationen

• Exceptional research/development experience with large-scale audio models (>3B parameters and >500k hours data).
• Strong understanding and hands-on experience with transformer architectures and/or diffusion models (incl. distillation/streaming).
• Proven ability to multi-node / multi-GPU distributed model training.
• Solid software engineering skills with production-quality code. Has shipped large-scale speech/audio models to production.
• Publications or notable open-source contributions in speech/audio/ML.

Aufgaben

• Architect, implement, pre-train, fine-tune, and post-train alignment for large-scale speech models.
• Independently lead small research projects while collaborating on larger initiatives.
• Design, run, and analyze experiments to advance model understanding.
• Develop and improve dev tooling to boost team productivity.
• Contribute to the full stack from low-level optimizations to high-level model design.
• Define data requirements and collaborate on data acquisition, labeling quality, and synthetic data strategies.
• Design automated evaluations and robustness/bias checks; conduct red-team studies.
• Harden training → evaluation → inference pipelines; monitor latency and cost; ensure SLAs.

Kenntnisse

Transformer models

Diffusion models

Distributed training

PyTorch

Profiling

Speech/audio ML

Tools

CUDA

Triton

C++

Python

PyTorch

Jobbeschreibung

# Machine Learning Engineer, TTSCantina LabsSalary not statedFull-timeremote· seniorEurope, USAnodepytorchListed via Jobicy · posted 10 Nov 2026. The application happens there, not on DevConnect.Apply on Jobicy## DescriptionAbout CantinaCantina 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.About the Role: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 TTS and adjacent tasks (voice cloning, controllable TTS, voice conversion 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.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.-Project Leadership: Independently lead small research projects while collaborating on larger team initiatives.-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.-GPU Scaling: Partner with infrastructure to run distributed training/inference on cloud fleets and productionize models with reliability and observability.-Safety & Responsibility: Contribute to safety/consent guardrails and to misuse/abuse mitigation for responsible speech technology.What You’ll Bring:-Exceptional research/development experience with large scale audio models (>3B models and >500k hours data).-Exceptional understanding and hands-on experience with transformer architectures and/or diffusion models (inc. distillation and streaming) and/or audio language modelling.-Strong experience with multi-node and multi-gpu distributed model training.-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 models to production.-Background in working with large-scale ML data.-Ability to iterate on data,, and triangulate quality using subjective and objective signals.-Notable publications and/or open source contributions in speech/audio/ML.-Experience with voice-cloning, speech-control, voice-generation.Preferred Experience:-Shipped large scale speech/audio models (TTS/VC/ASR) to production.-Work on large-scale ML systems.-Experience with audio language modelling, transformer architectures.-Experience with voice-cloning, speech-control, voice-generation.-Background in processing large-scale ML data.-Publications or notable open-source in speech/audio/ML.Compensation: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!