L’offerta in breve

Cantina: Machine Learning Engineer, Ops. Lavoro da remoto nell’UE, aperto a candidati in Italia. Contratto: Full-time. Tecnologie indicate: Python, Kubernetes, PyTorch.

Responsabilità e requisiti sono riportati nel riepilogo editoriale qui sotto, nella lingua disponibile. Verifica i dettagli nell’annuncio dell’azienda prima di candidarti.

Sul ruolo

Cantina is hiring a Machine Learning Engineer, Ops to productionize text-to-speech and speech recognition models. The research team supplies trained checkpoints; this role turns them into low-latency, real-time streaming services and owns the inference stack, Kubernetes infrastructure, and validation needed to release changes safely. It connects model research with production operations for a social AI platform focused on expressive, interactive experiences.

The work spans inference engine optimization, GPU performance, model accuracy regression testing, deployment, CI/CD, observability, and cost measurement. Candidates should have hands-on experience deploying and scaling ML models in production, with Python, PyTorch, GPU profiling, Kubernetes, cloud infrastructure, and model-serving knowledge. Experience with speech or audio models and frameworks such as vLLM, SGLang, TensorRT-LLM, or Triton is relevant.

Highlights

Optimize streaming TTS and ASR inference for latency and throughput.
Deploy and operate GPU services on Kubernetes.
Validate numerical parity and model accuracy across releases.
Track performance, utilization, and cost per request.

Questo recap è un riassunto editoriale di dataskew, non il testo dell'azienda.