cantina - Machine Learning Engineer, TTS
Requirements
• 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. • Shipped large scale speech/audio models (TTS/VC/ASR) to production. • Work on large-scale ML systems. • Experience with audio language modelling, transformer architectures. • Background in processing large-scale ML data. • Publications or notable open-source in speech/audio/ML.
Responsibilities
• 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.
Benefits
• 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. • 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 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!
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