ML Engineer

Key Responsibilities

• Design, develop, and deploy machine learning models for

  speech recognition and audio processing

  .
• Customize and fine-tune models using

  TensorFlow

  , focusing on training and evaluation pipelines.
• Work with

  OpenAIs Whisper ASR model,

  adapting it for specific use cases and datasets.
• Build robust and scalable data pipelines for preprocessing audio and text data.
• Collaborate with data scientists, backend engineers, and product teams to deliver ML-powered features.
• Optimize models for performance, accuracy, and latency in production environments.
• Stay up-to-date with advancements in deep learning, speech recognition, and ASR frameworks.

Preferred candidate profile

5+ years of experience

• Strong programming skills in

  Python

  and familiarity with modern Python ML libraries.
• Hands-on experience with

  TensorFlow

  , including custom model building and training.
• Familiarity with audio processing libraries (e.g., librosa, torchaudio) is a plus.
• Solid understanding of ML best practices, including data preprocessing, model evaluation, and deployment.
• Experience with tools such as Git, Docker, and cloud platforms (AWS/GCP) is a bonus.
• Bachelors or Master’s degree in Computer Science, Machine Learning, or a related field.