▷ (25/06/2024) Artificial Intelligence Engineer

2 weeks ago

Hyderabad, India Live Connections Full time
Role - AI / ML Engineer in PID / Speech

Experience - 5 to 7 years

Relevant Experience - 3 years minimum

Work Location - Hyderabad

Work Mode - Work From Office (WFO) Hybrid

Notice Period - Immediate to 30 days

Must Have

- 3 years of experience in Speech Processing, NLP & AI/ML algorithm development

Applicants can share your resumes to

Requirements:

- A strong programming background, in languages such as Perl, Java, Python, and C, and facility with computational algorithms are essential. Coursework in statistics and experience in using machine learning toolkits are highly desirable.- Experience with machine learning and deep learning frameworks (like Tensorflow, Keras or PyTorch) and libraries (like scikit-learn)- Experience with state-of-the-art speech representation models and recognition toolkits and models like Kaldi, Wav2Vec, Whisper, etc.- Experience with large language models like ChatGPT, Llama, Vicuna, etc. is highly desirable.- Experience with cloud-based (AWS) deployment of models, performance monitoring and issues troubleshooting- Excellent verbal and written communication

Responsibilities:

- Design and develop innovative feature models for automated assessment, learning and feedback solutions by analysing acoustic and language aspects of speech through research in NLP and speech processing.- Design, develop and/ or improve core speech technology components such as automatic speech recognition, speaker and language recognition, speech enhancement, etc.- Behaviour modelling for emotion recognition, engagement modelling and other traits identification/ modelling from speech and language for multi-modal solutions- Design and develop innovative feature models using Large Language Models (LLMs) for conversational scenarios powered by spoken dialog systems capabilities- Leverage self-supervised and unsupervised speech representation models for development of speech skills feedback features- Engineer large models to reduce complexity and latency for real-time processing- Implement effective methods of AI/ML model testing during development, deployment, and recalibration- Utilize best practices around design, coding, automated unit, regression testing, and deployment of AI/ML models to production, and responsible use of AI- Keeping up-to-date with latest advancements in AI / NLP / Speech research- Work effectively in the agile-at-scale framework- Clearly communicate findings to business stakeholders

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