Join Cantina as a Machine Learning Engineer to build advanced speech systems and contribute to innovative AI technology.
Posted by employer 4 months ago
First seen on Joblaze 1 week ago
Last verified on the company career page 1 day ago
Skills & Technologies
Role intensity
70% hands-on coding
AI in the day-to-day
Contribute to the development of safe, steerable, and trustworthy AI systems.
Requirements
- Experience
- 5+ years
Not disclosed in this posting: work arrangement, visa sponsorship.
Benefits
Joblaze summary
The Machine Learning Engineer for Cantina's Speech Team will focus on developing advanced text-to-speech systems, overseeing the entire process from model architecture to production deployment. Key skills include expertise in large-scale audio models, proficiency in transformer architectures, and strong software engineering capabilities, particularly with PyTorch. This role is ideal for experienced engineers with a background in machine learning and audio processing, who are eager to contribute to innovative AI solutions in a dynamic startup environment.
Joblaze insights
- Listed 9 days ago on Joblaze — tracked directly from Cantina's career page.
- Cantina has 21 other open roles including Research Scientist, Video Foundation Models, Research Intern, Machine Learning Intern.
- 1661 active C++ roles on Joblaze right now.
- 481 active PyTorch roles on Joblaze right now.
- 102 active CUDA roles on Joblaze right now.
- Salary band is in line with the typical range for AI/ML roles (median ~$188,000).
- Pays more than 86% of the 808 salaried C++ roles we track (median $150,000). See C++ salary trends
Quick facts
- What's the salary range?
- Cantina lists $200,000–$220,000 for this role.
- How much experience is required?
- At least 5 years of relevant experience for this Machine Learning Engineer, TTS role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: C++, CUDA, Diffusion Models, PyTorch, speech control, transformer architectures.
- What seniority level is this role?
- Cantina targets senior candidates for this position.
- Is this full-time or contract?
- Full-time for this Machine Learning Engineer, TTS role at Cantina.
From the original posting
About Cantina
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.
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:
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!