Troubleshoot and resolve complex issues across ASR, TTS, ALM, and S2S pipelines
Model Integration: Work alongside Model researchers to transition ASR, TTS and S2S models from research to production readiness.
Develop Core Speech Services: Build and enhance C++ & python backend implementations for ASR, TTS, and S2S pipelines, leveraging CUDA for GPU acceleration
Optimize Inference Performance: Improve streaming latency and throughput through advanced batching strategies, encoder caching, and multi-threaded pipeline optimizations
Feature Development: Add new capabilities such as advanced voice activity detection, speaker diarization, decoder implementations (CTC, WFST, Flashlight), and text post-processing
Client Libraries: Contribute to Python and C++ client SDKs and CLI tools for easy service integration
Assist with API integration, SDK usage, model deployment, and performance optimization
Provide advanced technical guidance to customers implementing speech technology solutions
What we need to see
Masters or BE/BTech in Computer Science, computer architecture, or related field
6+ years of experience
Excellent C++ & Python programming and software design skills, including debugging, performance analysis, and test design.
Experience with inference pipelines for LLM, Speech Recognition & Speech Synthesis
Solid understanding of modern model architectures (Transformers, CNNs, RNNs)
Excellent debugging abilities spanning multiple software (storage systems, kernels and containers)
Experience building and deploying cloud services using HTTP REST, gRPC, Websockets and related technologies
Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic matrix environment
Ability to work independently, define project goals and scope and manage your own development effort.
Knowledge of real-time streaming audio systems and low-latency architectures
Experience with speech model fine-tuning or customization
Ways to stand out from the crowd
Publications or contributions to ML optimization open-source projects.
Experience with embedded systems or edge deployment
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
