Widely considered to be one of the technology world’s most desirable employers, NVIDIA is an industry leader with groundbreaking developments in High-Performance Computing, Artificial Intelligence and Visualization.

The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services.

GPU deep learning ignited modern AI the next era of computing with the GPU acting as the brain of computers, robots, autonomous cars and conversational AI that can perceive and understand the world.

Today, we are increasingly known as the AI computing company. We're looking to grow our company, and build our teams with the smartest people in the world.

Join us at the forefront of technological advancement.

NVIDIA is looking for Speech Data Engineers to develop high-impact, high-visibility Speech AI product "Riva" & improve the experience of millions of customers.

If you're creative & passionate about solving real world conversational AI problems, come join our Riva Product engineering team.

For more details on Riva check https : / / developer.nvidia.com / riva

What you’ll be doing :

Build speech training data sets for text-to-speech (TTS) systems

Develop WFST and Neural networks-based Text-Normalization and Inverse Text-Normalization

Use and extend internal MLOps tooling to scale model development and automate cross-team work

Apply data science techniques to characterize model performance and quality metrics across platforms for various speech AI components and identify areas for improvement

Collaborate with other engineers and scientists in data collection and development efforts

Write clear and concise documents (e.g. analysis reports)

Collaborate with various teams on new product features and improvements of existing products

Participate in developing and reviewing code, design documents, use case reviews, and test plan reviews

Help innovate, identify problems, recommend solutions and perform triage in a collaborative team environment

What we need to see :

Bachelor's degree or Master’s degree (or equivalent experience) or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, or Applied Math

Knowledge of scripting languages (e.g. Python, bash)

Knowledge of phonetics / phonology and ability to analyze / validate phonetic transcriptions

Background with WFST

Experience with Pytorch

Experience with building ASR, NLP, and speech synthesis models

Excellent written and spoken communication skills

Experience with MLOPS workflows & traceability and versioning of datasets

Understanding of MLOPS life cycle

General background around version control and code review tools like Git, Gerrit.

Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic matrix environment

Ways to stand out from the crowd :

Master’s in Computational Linguistics (or equivalent field with computational emphasis); alternatively, 2 years of experience in the field.

Hands-on experience on Speech Technologies like Text to Speech, Automatic Speech Recognition, Speech Command detection etc

Experience in writing grammars and building FSTs

Strong personal interest in learning, researching, and creating new technologies related to foreign languages, linguistics, phonetics, phonology and language technology

Feeling comfortable and motivated when working in a fast paced, highly collaborative, dynamic work environment

Strong C++ programming skills.

Background with Dockers and Kubernetes

Background with deploying machine learning models on data center, cloud, and embedded systems

Native or near-native fluency in a non-English language - Spanish / Mandarin / German / Japanese / Russian / French / UK English / Arabic / Hindi / Korean / Italian / Portuguese

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.