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NVIDIA
NVIDIA

Pioneering accelerated computing and AI

Senior Deep Learning Scientist, Speech Synthesis

직무머신러닝
경력시니어급
위치Vietnam
근무오피스 출근
고용정규직
게시1주 전
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NVIDIA is a global leader in AI, high-performance computing, and visualization, with GPU technology powering everything from modern computers to robots and autonomous systems. As a pioneer in AI computing, NVIDIA is shaping the future of conversational AI.

NVIDIA is looking for Speech Data Scientists to develop the high‑impact, high‑visibility Speech AI product Riva and improve the experience of millions of customers. If you're creative and passionate about solving real‑world conversational AI problems, come join our Riva Product Engineering team.

More details: https://developer.nvidia.com/riva

What you'll be doing:

  • Train Speech Synthesis mel-spectrogram and vocoder models.

  • Measure, benchmark, and analyze model performance, accuracy, and bias; recommend improvements.

  • Maintain the TTS model evaluation system and characterize quality metrics across platforms.

  • Improve processes for speech data processing, augmentation, filtering, and TTS training set preparation.

  • Build knowledge of TTS datasets for training and evaluation.

  • Collaborate with cross-functional teams on new features, improvements, and issue triage.

  • Participate in code reviews, design reviews, use case reviews, and test plan reviews.

What we need to see:

  • Master’s degree (or equivalent experience) or PhD in Computer Science, Electrical Engineering, AI, Applied Math, Linguistics, or Computational Linguistics.

  • 5+ years of experience in machine learning and AI model development.

  • Strong Python programming skills, with solid fundamentals in software design and optimization.

  • Strong knowledge of ML/DL techniques and tools, including CNNs, RNNs/LSTMs, and Transformers.

  • Hands-on experience training speech synthesis models, including TTS, voice cloning, or speech-to-speech systems.

  • Proficiency with Py Torch and familiarity with DSP and feature extraction techniques (FFT, MFCC, Mel spectrograms).

  • Experience with Git, Gerrit, or GitLab, and strong collaboration skills.

Ways to stand out from the crowd:

  • Experience with multilingual or code-switched TTS, voice cloning, or cross-lingual voice cloning.

  • Familiarity with text normalization, inverse text normalization, and multilingual G2P systems.

  • Interest in linguistics, phonetics, phonology, and language technologies.

  • Strong C++ programming skills and familiarity with CUDA, cuDNN, or TensorRT.

  • Experience deploying ML models on data center, cloud, or embedded systems.

NVIDIA is committed to fostering a diverse work environment and is proud to be an equal opportunity employer. We do not discriminate based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.

Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/

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NVIDIA 소개

NVIDIA

NVIDIA

Public

A computing platform company operating at the intersection of graphics, HPC, and AI.

10,001+

직원 수

Santa Clara

본사 위치

$4.57T

기업 가치

리뷰

10개 리뷰

4.4

10개 리뷰

워라밸

2.8

보상

4.5

문화

4.2

커리어

4.3

경영진

3.8

78%

지인 추천률

장점

Cutting-edge technology and innovation

Excellent compensation and benefits

Great team culture and collaboration

단점

High pressure and expectations

Poor work-life balance and long hours

Fast-paced environment leading to burnout

연봉 정보

79개 데이터

L3

L4

L5

L3 · Data Scientist IC2

0개 리포트

$177,542

총 연봉

기본급

-

주식

-

보너스

-

$150,910

$204,174

면접 후기

후기 5개

난이도

3.0

/ 5

면접 과정

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

자주 나오는 질문

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience