Audio Machine Learning Engineer

Qualcomm · Hyderabad · 2+ yrs experience · Posted 2026-02-20

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About the role

Qualcomm India Private Limited
Engineering Group, Engineering Group > Systems Engineering
Responsibilities: - The Advanced Tech R&D team is looking for a research engineer with a passion for machine learning appli ed to generative audio and natural language use cases.
- You will be working with a team of machine learning experts to develop advanced technology and solutions for EdgeAI mobile phone s headset s and variety of IoT device s
- The team includes and works with algorithm hardware and software engineers across company to
- develop port newly designed solutions to real live prototypes shown at tradeshows and other customer events and support commercialization activities in upcoming products
- Develop innovative machine learning algorithms for Aud io and speech generative models
- After successful demos to technical and business audiences, work with commercialization teams to transfer and deploy newly developed solutions onto Qualcomm platforms and customer devices ile corresponding papers and patent disclosures; achieve state-of-the-art performance and beyond in various audio and speech applications
Qualifications: - R&D experience of audio and speech generative networks audio/speech synthesis speech restoration kind of models
- Familiarity with recent trends in machine learning ( diffusion models U-Nets Transformer BERT, BART etc.) and traditional statistical modeling/feature extraction techniques
- Proficiency in designing implementing and training DL algorithms in high-level languages/frameworks ( e.g.
- PyTorch TensorFlow)
- Willingness to engage in hands-on R&D in modeling of audio speech data
- Working in cross disciplinary geographically-dispersed teams
- Master's degree Phd in Electronics/ Computer Electrical Engineering
- 2+ years of R&D experience in audio/speech model development in academic/industry
- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
- Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience.
- PhD in Engineering, Information Systems, Computer Science, or related field.

Qualifications

- R&D experience of audio and speech generative networks audio/speech synthesis speech restoration kind of models
- Familiarity with recent trends in machine learning ( diffusion models U-Nets Transformer BERT, BART etc.) and traditional statistical modeling/feature extraction techniques
- Proficiency in designing implementing and training DL algorithms in high-level languages/frameworks ( e.g. PyTorch TensorFlow)
- Willingness to engage in hands-on R&D in modeling of audio speech data
- Working in cross disciplinary geographically-dispersed teams
- Master's degree Phd in Electronics/ Computer Electrical Engineering
- 2+ years of R&D experience in audio/speech model development in academic/industry
- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
- Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience.
- PhD in Engineering, Information Systems, Computer Science, or related field.

Responsibilities

- The Advanced Tech R&D team is looking for a research engineer with a passion for machine learning appli ed to generative audio and natural language use cases.
- You will be working with a team of machine learning experts to develop advanced technology and solutions for EdgeAI mobile phone s headset s and variety of IoT device s
- The team includes and works with algorithm hardware and software engineers across company to
- develop port newly designed solutions to real live prototypes shown at tradeshows and other customer events and support commercialization activities in upcoming products
- Develop innovative machine learning algorithms for Aud io and speech generative models
- After successful demos to technical and business audiences, work with commercialization teams to transfer and deploy newly developed solutions onto Qualcomm platforms and customer devices ile corresponding papers and patent disclosures; achieve state-of-the-art performance and beyond in various audio and speech applications

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