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.
