Machine Learning Engineer

• Architect, implement, pre-train, fine-tune, and post-train/alignment large-scale speech models
• Independently lead small research projects while collaborating on larger team initiatives
• Design, run, and analyze scientific experiments
• Develop and improve development tooling
• Contribute across the stack, from low-level optimizations to high-level model design
• Define data requirements and collaborate on acquisition, curation, augmentation, labeling quality, and synthetic data strategies
• Design automated objective and subjective evaluations, including listening tests, SV/WER/ASR-based metrics, robustness and bias checks, and red-team studies
• Harden the training-to-evaluation-to-inference pipeline; profile latency, memory, and cost; and meet production SLAs with monitoring and rollback
• Partner with infrastructure on distributed training/inference on cloud fleets and productionize models with reliability and observability
• Contribute to safety/consent guardrails and misuse/abuse mitigation for responsible speech technology

Explore Machine Learning Engineer, TTS at Cantina. Review requirements and application details.