What We’re Looking For
We are seeking a highly motivated graduate student to join our team. This internship offers a unique opportunity to apply your research skills to real-world problems in speech recognition and audio processing. You will work closely with our experienced engineers to enhance our ASR capabilities and contribute to cutting-edge technology that impacts millions of users globally.
Responsibilities
Assist in developing, training, and optimizing machine learning models for automatic speech recognition.
Conduct research to improve model accuracy and performance using large datasets of audio recordings.
Collaborate with the engineering team to integrate new models and algorithms into the Tarteel app.
Utilize PyTorch and NVIDIA NeMo frameworks for model development and experimentation.
Participate in managing computational resources using SLURM.
Work with Amazon S3 for data storage and retrieval.
Apply audio processing techniques for data preprocessing and augmentation.
Present research findings and progress updates to the team.
Stay informed about the latest advancements in speech recognition and machine learning.
Qualifications
Currently enrolled in or completed a graduate program in Computer Science, Electrical Engineering, or a related field.
Strong foundation in machine learning and deep learning concepts.
Proficiency in Python and experience with PyTorch.
Familiarity with NVIDIA NeMo or similar frameworks for speech recognition.
Understanding of SLURM workload manager and Amazon S3.
Experience with audio signal processing techniques.
Proven ability to work with large-scale datasets.
Excellent problem-solving skills and attention to detail.
Strong communication skills and ability to work collaboratively.
Preferred Qualifications
Research experience in automatic speech recognition or related areas.
Publications or projects demonstrating expertise in machine learning and audio processing.
Familiarity with natural language processing and language modeling.
Understanding of Quranic recitation and its nuances (desirable but not mandatory).
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