Speech AI Solutions Architect - Multilingual & Real-Time

NVIDIA Corporation; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

NVIDIA Corporation is seeking a Solutions Architect to help customers in South East Asia adopt NVIDIA speech AI technologies. You will design architectures, run workshops, and enable partners across cloud, data center, and edge deployments.

Responsibilities include translating requirements into deployable solutions, validating models, and delivering technical sessions to accelerate adoption of NVIDIA speech AI such as Riva and related microservices.

Qualifications

• BS, MS, or PhD in Computer Science or related field or equivalent experience.
• 5+ years of proven experience in building and deploying speech, multimodal AI, or LLM systems.
• Strong Python skills and experience with PyTorch.
• Hands-on experience with ASR, TTS, speech understanding, or multimodal models.
• Experience with latency, quality, and scale trade-offs.
• Familiarity with Docker, Kubernetes, Helm, or equivalent tooling.
• Ability to design and explain end-to-end speech AI pipelines.
• Strong communication across customers, partners, product management, and engineering.

Responsibilities

• Develop voice AI solutions addressing real-time transcription and multilingual scenarios.
• Support solution development and technical validation around NVIDIA speech AI models.
• Translate customer requirements into deployable architectures and feedback.
• Assist deployment of NVIDIA Riva, Nemotron, and NIM microservices across cloud, data center, and edge.
• Deliver demos, workshops, and partner enablement sessions to accelerate adoption.

Skills

Python

PyTorch

ASR/TTS

Multimodal AI

Communication

Education

BS/MS/PhD in Computer Science or related field

Tools

Docker

Kubernetes

Helm

Job description

NVIDIA Corporation is seeking a Solutions Architect to help customers in South East Asia adopt NVIDIA speech AI technologies. You will design architectures, run workshops, and enable partners across cloud, data center, and edge deployments.

Responsibilities include translating requirements into deployable solutions, validating models, and delivering technical sessions to accelerate adoption of NVIDIA speech AI such as Riva and related microservices.