At a Glance
- Tasks: Build cutting-edge speech systems and lead innovative research projects.
- Company: Join Cantina, a pioneering social platform with advanced AI technology.
- Benefits: Competitive salary, generous equity, comprehensive health insurance, and 42 days of paid time off.
- Other info: Dynamic work environment with opportunities for growth and innovation.
- Why this job: Shape the future of AI in creativity and social interaction while making a real impact.
- Qualifications: Experience with large-scale audio models and strong software engineering skills required.
The predicted salary is between 170000 - 190000 £ per year.
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
Machine Learning Engineer, TTS in London employer: Cantina Labs
Cantina Labs is an exceptional employer that fosters a vibrant work culture focused on innovation and creativity in the realm of social AI. With generous benefits including competitive salaries, extensive paid time off, and comprehensive health coverage, employees are empowered to thrive both personally and professionally. The collaborative environment encourages growth and development, making it an ideal place for those passionate about shaping the future of AI and storytelling.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer, TTS in London
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We think you need these skills to ace Machine Learning Engineer, TTS in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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How to prepare for a job interview at Cantina Labs
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
