Machine Learning Engineer (Speech) - AI (Remote,India)

India

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Level AI

Level AI's call center AI uses semantic intelligence to understand support interactions to improve contact center team performance. Request a demo today.

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Level AI is a Series B funded Mountain View, CA-based startup innovating in the Voice AI space. We are backed by top VCs, technologists from Silicon Valley, and industry experts. We are on a mission to revolutionize the customer sales experience for businesses. We are innovating in speech AI, NLP/NLU, and information retrieval systems to bring customers and businesses closer to one another.

As a critical member of the team, your work will be cutting-edge technologies and will play a high-impact role in shaping the future of AI-driven enterprise applications. You will directly work with people who've worked at Amazon, Facebook, Google, and other technology companies in the world. With Level AI, you will get to have fun, learn new things, and grow along with us.

Roles and Responsibilities :

  • Work on problems arising in speech-to-text pipelines, such as voice activity detection, transcription, automatic speech recognition (ASR) speaker diarization (SD),.
  • Train, deploy and maintain scalable speech-to-text pipeline  to power Level AI’s ASR engine.
  • Keep abreast with SOTA techniques in your area and exchange knowledge with colleagues.
  • Work with other team members to develop architecture & design of systems.
  • Ability to independently conduct experiments with model architectures, training schemes, and approaches proposed in ASR literature. 
  • Work in an agile environment to deliver high-quality products.

Requirements :

  • Bachelors in Computer Science or Electrical Engineering or related fields.
  • Strong knowledge of Machine Learning fundamentals and Deep learning architectures like Transformer, Conformer etc… 
  • Understanding of Classical Speech processing models like gaussian mixture models(GMM) and Hidden Markov models(HMM).  
  • Understanding of  Connectionist temporal classification (CTC) and RNN-T objective functions.
  • Hands-on building n-gram language model & integrating with shallow fusion techniques. 
  • Hands-on experience with Python programming language and a Deep Learning framework like Pytorch/Tensorflow.
  • Hands-on experience in deploying end-to-end speech recognition models using cloud applications like AWS, GCP.
  • Awareness of state of the art research in speech recognition and Signal processing communities.
  • Experience in Semi-supervised learning is a plus.  
  • Experience in building text-to-speech or punctuation restoration for ASR transcript models is a plus.

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Agile Architecture ASR AWS Classification Computer Science Deep Learning Engineering GCP Machine Learning NLP Pipelines Python PyTorch Research RNN TensorFlow

Perks/benefits: Startup environment

Regions: Remote/Anywhere Asia/Pacific North America
Countries: India United States
Job stats:  63  14  0

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