Highlights
Develop cutting-edge speech-to-text models, integrate seamlessly with cloud services, ensure data compliance.
Description
Job Summary
pWe are seeking a skilled AI/ML Engineer to develop, optimize, and maintain advanced speech recognition models for medical transcription. This role involves building NLP pipelines, implementing error detection, integrating with cloud services, and ensuring data compliance.
Responsibilities
- Develop and fine-tune speech recognition models for various accents.
- Create NLP pipelines for understanding medical terminology and context.
- Implement QA automation in transcription outputs.
- Integrate with voice services like AWS Transcribe Medical or Azure Cognitive Speech.
- Build APIs for seamless integration with EMR/EHR systems.
- Collaborate with QA teams to improve model accuracy.
- Ensure data security and compliance.
Required Skills
- Python programming
- NLP & Machine Learning expertise
- Experience in speech recognition frameworks
- Transformer models knowledge
- Familiarity with cloud services
Required Skills Explained
- Strong knowledge of Python, essential for implementing algorithms and models.
- Deep understanding of NLP & Machine Learning to develop advanced transcription systems.
- Experience with speech recognition frameworks such as Whisper, Vosk, DeepSpeech, or Kaldi to fine-tune models specifically for medical applications.
- Familiarity with transformer models like BERT, BioBERT, ClinicalBERT, and GPT-based NLP for handling complex medical terminologies.
- Experience with Git for managing code versions and collaborating with team members.
- Knowledge of cloud services (AWS, Azure, or GCP) to deploy and manage AI/ML models securely.
Who is this for
pThis position is ideal for candidates with a strong background in AI/ML, NLP, and speech recognition. Experience working on medical transcription projects would be advantageous.
Why This Job is a Good Opportunity
ulliCollaborate on cutting-edge speech-to-text technologies that enhance the accuracy and efficiency of medical document transcription.liWork with diverse data sets from various accents, ensuring global applicability and inclusivity.liLeverage your expertise to improve patient care by contributing to better communication between healthcare providers and patients through accurate documentation.liGrow professionally in a dynamic environment where you can experiment with new models and technologies.
Interview Preparation Tips
- Prepare examples of projects or experiences related to AI/ML, NLP, and speech recognition.
- Be ready to discuss your experience with specific tools like Whisper, Vosk, DeepSpeech, Kaldi, and transformer models such as BERT and GPT.
- Highlight your understanding of data security and compliance standards like HIPAA/GDPR in model training and storage.
- Practice explaining technical concepts in simple terms to demonstrate clear communication skills.
Career Growth in This Role
pThis role offers numerous opportunities for professional growth. As you work on fine-tuning models, you can explore advanced topics such as LLM fine-tuning or prompt engineering. The ability to integrate with various voice services and EMR/EHR systems can lead to a broader scope of projects. Additionally, collaborating closely with QA and transcription teams will help you develop leadership skills in managing cross-functional teams.pGiven the increasing demand for AI/ML solutions in healthcare, this role positions you well for future advancements in speech technology and NLP applications within medical fields.
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Skills
Frequently Asked Questions
What experience is required?1-3 years in AI/ML, NLP, or Speech Recognition. Freshers with strong projects are welcome.
What technical skills do you need?Python, NLP & ML expertise, speech recognition frameworks, transformer models, and cloud services experience.
Is medical terminology knowledge necessary?While not mandatory, familiarity with medical terminologies is an added advantage.
