[All remote jobs](https://jobicy.com/jobs.md)[![Cantina Labs logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2026/11/e52bb5e84323-221.webp)](https://jobicy.com/company/cantina-labs.md)[Cantina Labs](https://jobicy.com/company/cantina-labs.md) # Machine Learning Engineer, TTS AI Summary Cantina Labs is hiring a senior Research/ML Engineer to develop production-grade text-to-speech and adjacent speech-generation systems. The role spans speech-model architecture, large-scale training, data strategy, evaluation design, inference optimization, and production reliability. The engineer will independently lead smaller research projects while working with research, data, and infrastructure partners on distributed GPU workloads. Strong hands-on experience with large audio models, PyTorch, transformer or diffusion architectures, and shipped speech systems is essential. The position also includes responsible-AI work such as consent guardrails, robustness testing, and misuse mitigation for voice technology.[Apply for this job](#job-application)[View company](https://jobicy.com/company/cantina-labs.md)ShareRemote from[USA](https://jobicy.com/job-region/usa.md), [Europe](https://jobicy.com/job-region/europe.md)SalaryUndisclosedDepartment[Data Science & Analytics](https://jobicy.com/categories/data-science.md)EmploymentFull TimeExperienceSeniorPublished10 Nov 2026Apply before10 Dec 2026Listing views44Application actions4Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. Opportunity details ## About this role. ### 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: 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! Show more [Apply now >](https://jobicy.com/jobs/160994-machine-learning-engineer-tts.md) > Annual salary information is not provided for this position. Explore salary ranges for similar roles in our [Salary Directory ›](https://jobicy.com/salaries.md) * ![Upload CV](data:image/svg+xml;base64,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) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThis is an exceptionally demanding senior ML role requiring proven experience training and shipping multi-billion-parameter speech models at scale. It combines research depth, high-performance engineering, distributed systems, rigorous evaluation, and safety considerations. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Highly competitive$240,000US market range (per year)$180k–$300k0$330k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer base-pay range is disclosed; “competitive salary” and the $500/month lifestyle spending account are not salary figures. Estimated annual US-market base salary for a senior production speech/ML engineer is $180,000–$300,000 USD, with an estimated midpoint of $240,000 USD. The yearly cadence is inferred from the full-time senior professional role and US market conventions. ## Core skills Skills and capabilities most closely associated with this opportunity. [Text-to-Speech (TTS)](https://jobicy.com/jobs?search_keywords=Text-to-Speech%20TTS.md)[Speech Machine Learning](https://jobicy.com/jobs?search_keywords=Speech%20Machine%20Learning.md)[PyTorch](https://jobicy.com/jobs?search_keywords=PyTorch.md)[Transformer Architectures](https://jobicy.com/jobs?search_keywords=Transformer%20Architectures.md)[Diffusion Models](https://jobicy.com/jobs?search_keywords=Diffusion%20Models.md)[Distributed Training](https://jobicy.com/jobs?search_keywords=Distributed%20Training.md)[Multi-GPU Training](https://jobicy.com/jobs?search_keywords=Multi-GPU%20Training.md)[CUDA Optimization](https://jobicy.com/jobs?search_keywords=CUDA%20Optimization.md)[Triton](https://jobicy.com/jobs?search_keywords=Triton.md)[Audio Language Modeling](https://jobicy.com/jobs?search_keywords=Audio%20Language%20Modeling.md)[Voice Cloning](https://jobicy.com/jobs?search_keywords=Voice%20Cloning.md)[Speech Model Evaluation](https://jobicy.com/jobs?search_keywords=Speech%20Model%20Evaluation.md)[ML Data Curation](https://jobicy.com/jobs?search_keywords=ML%20Data%20Curation.md)[Inference Optimization](https://jobicy.com/jobs?search_keywords=Inference%20Optimization.md)[MLOps](https://jobicy.com/jobs?search_keywords=MLOps.md) Sample interview questionsHow would you design an end-to-end evaluation framework for a production TTS model?I would combine objective measures such as WER through ASR, speaker-verification similarity, latency, and failure rates with structured human listening tests for naturalness, intelligibility, prosody, and speaker similarity. I would segment results by language, accent, input type, and difficult edge cases, then use dashboards and regression gates to prevent quality or safety regressions before release. Describe your approach to scaling training for a multi-billion-parameter speech model across multiple GPU nodes. I would first profile memory, communication, and input-pipeline bottlenecks, then select an appropriate parallelism strategy such as FSDP, tensor parallelism, or pipeline parallelism. I would use mixed precision, checkpointing, efficient data sharding, fault-tolerant checkpoints, and monitoring for throughput, loss stability, GPU utilization, and communication overhead. How do you balance model quality, inference latency, and serving cost for TTS? I start with explicit product quality and latency targets, profile the full serving path, and identify the highest-cost model components. Depending on findings, I may apply distillation, quantization, streaming generation, batching, caching, kernel optimization, or architecture changes, validating each trade-off with both objective metrics and listening evaluations. What safeguards would you implement for a voice-cloning product? I would build consent verification and provenance controls into the data and enrollment flows, restrict cloning of protected or unverified voices, and maintain audit logs and abuse-reporting processes. I would also red-team impersonation risks, monitor for suspicious usage patterns, establish clear escalation paths, and continuously evaluate whether safeguards are effective. Tell us about a time you used experimental results to change an ML data strategy. In a strong example, I would compare model failures across data slices and use listening tests plus objective metrics to identify gaps such as noisy labels, insufficient speaker diversity, or weak coverage of difficult phonetic contexts. I would then prioritize targeted curation, augmentation, relabeling, or synthetic-data generation, run controlled retraining experiments, and retain only interventions that improve the relevant quality and robustness measures. Next step ## Apply now. Follow the employer’s application method and review Jobicy’s safety guidance before sharing personal information. Keep exploring ## Related remote jobs. * ![Deepgram logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2020/12/WRILS-201212160008-406229.jpg) Deepgram Nov 10 New ### [Director of Research, Text-to-Speech](https://jobicy.com/jobs/161053-director-of-research-text-to-speech.md) Company Overview Deepgram is bringing the world’s most natural interface, voice, to the technology we use every day. 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