Deevia Software India
Audio AI Developer
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
Bengaluru, Karnataka, India
Work mode:
Onsite
Published on:
10 September 2026
What they need
Experience
2 to 5 years of experience, with at least 2+ years of hands-on experience in Speech-to-Text (ASR) and Language Model development.
Job Summary
We are looking for a highly motivated AI Audio/Speech Developer with strong expertise in Deep Learning, Speech Recognition, and Large Language Models. The ideal candidate should be capable of independently designing, training, fine-tuning, and optimizing AI models from scratch, implementing research papers, and developing state-of-the-art speech and language solutions.
Key Responsibilities
- Design and develop Speech-to-Text (ASR) and language processing solutions using Deep Learning techniques.
- Build, train, fine-tune, and optimize transformer-based models from scratch.
- Implement and reproduce advanced research papers related to speech recognition, NLP, and Generative AI.
- Work on LLM and SLM architectures, model adaptation, quantization, and deployment optimization.
- Develop and improve speech recognition pipelines for accuracy, latency, and resource efficiency.
- Perform model evaluation, benchmarking, and performance tuning.
- Collaborate with cross-functional teams to integrate AI models into production applications.
- Stay updated with the latest advancements in Speech AI, LLMs, and Generative AI technologies.
Required Skills
Technical Skills
Strong knowledge of Deep Learning, Machine Learning, and Neural Network architectures.
Deep understanding of Transformer Architecture and Large Language Models (LLMs).
Hands-on experience with:
Automatic Speech Recognition (ASR)
Speech-to-Text systems
Language Models
Transformer-based architectures
Experience in training, fine-tuning, and optimization of ASR models.
Hands-on experience with:
LLM fine-tuning
Quantization
Model optimization
Parameter-efficient tuning techniques
Strong programming skills in Python.
Experience with PyTorch and/or TensorFlow.
Experience implementing research papers and converting them into production-ready solutions.
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