Machine Learning Engineer, TTS

Machine Learning Engineer, TTS

Full-Time 170000 - 190000 £ / year (est.) No working from home possible
Cantina Labs

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 collaboration.
  • 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 account – $500/month to use however you’d like.
  • Complimentary lunch and snacks for in-office employees.
  • One Medical membership, and more!

Machine Learning Engineer, TTS 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.

Cantina Labs

Contact Details:

Cantina Labs Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Machine Learning Engineer, TTS

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Cantina Labs or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Cantina Labs.

Tap into Online Developer Communities

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Explore Job Boards Specifically for Tech Roles

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We think you need these skills to ace Machine Learning Engineer, TTS

Machine Learning
Speech Systems Development
Model Building
Experimental Design
Data Evaluation
Tool Development
Full-Stack Contribution

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Cantina Labs.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Cantina Labs and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Cantina Labs

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Cantina Labs uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.