Research Engineer II

Research Engineer II

Job Summary

We are looking for a Research Engineer II to join our AI Research team to develop state-of the-art Speech and Natural Language Processing solutions for healthcare applications. The candidate will contribute to designing, developing, fine-tuning, and deploying Automatic Speech Recognition (ASR), Large Language Models (LLMs), and NLP systems while working closely with product and engineering teams. The ideal candidate should have hands-on experience with modern deep learning frameworks, Transformer architectures, speech recognition systems, and Generative AI techniques.

Responsibilities

• Design, develop, and fine-tune Automatic Speech Recognition (ASR) and Natural Language Processing (NLP) models.
• Develop hybrid and end-to-end speech recognition systems using modern deep learning techniques.
• Build multilingual speech recognition, language identification, speaker diarization, and audio classification systems.
• Design, train, and evaluate Transformer-based language models for NLP tasks including text classification, summarization, question answering, entity extraction, and information retrieval.
• Develop data preprocessing, annotation, augmentation, and quality improvement pipelines for speech and text datasets.
• Create synthetic datasets and perform data augmentation to improve model robustness and generalization.
• Fine-tune pretrained foundation models such as Whisper, wav2vec2, HuBERT, BERT, RoBERTa, T5, GPT, and Llama for downstream tasks.
• Design and implement efficient model training and inference pipelines using PyTorch and related frameworks.
• Evaluate model performance using appropriate metrics such as WER, CER, F1-score, Recall, Precision, BLEU, ROUGE, and Accuracy.
• Analyze production issues, investigate data drift, and improve model performance using continuous evaluation and retraining.
• Conduct experiments with state-of-the-art algorithms and publish technical findings where applicable.
• Work closely with Product Managers, Software Engineers, and Data Engineers to translate business requirements into scalable AI solutions.
• Document research methodologies, experiments, and model performance for internal knowledge sharing.
• Ensure compliance with organizational AI governance, privacy, and data security policies.
• Stay updated with recent advances in Speech AI, NLP, Large Language Models, and Generative AI.

Qualifications

• Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, Speech Processing, NLP, or a related field.
• Ph.D. is a plus.
• 2–4 years of hands-on experience developing and deploying AI/ML solutions.
• Strong understanding of Machine Learning, Deep Learning, and Transformer architectures.
• Hands-on experience in developing or fine-tuning Speech Recognition (ASR) and/or NLP models.
• Proficiency in Python and experience with PyTorch or TensorFlow.
• Experience with speech or NLP frameworks such as Hugging Face, Kaldi, SpeechBrain, ESPnet, or similar.
• Strong problem-solving, analytical, and communication skills.

Technical Skills

• Speech AI: ASR, Language Identification, Speaker Diarization, Audio Classification.
• NLP & LLMs: Transformer Models, BERT, T5, GPT, Whisper, wav2vec2, HuBERT.
• Programming: Python, Shell Scripting, Git.
• Frameworks: PyTorch, TensorFlow, Hugging Face Transformers.
• Platforms: Linux.

Soft Skills

• Strong analytical and problem-solving abilities.
• Excellent communication and documentation skills.
• Ability to work independently and collaboratively in cross-functional teams.
• Research-oriented mindset with continuous learning.
• Ability to manage multiple projects and meet deadlines.