ML Engineer

Job Description

Voicecare AI is a Healthcare Administration General Intelligence (HAGI) company for the back-office and the RCM industry. We are building a safety focused large and small conversational language model for the healthcare industry. Our mission is to dramatically improve access, adherence, and outcomes for the patients and the healthcare workforce through the application of generative AI. We are a venture-backed company partnering with the top healthcare stakeholders in the country.

We are seeking a Machine Learning & NLP Engineer to drive the development of large language models (LLMs), deep learning architectures, and speech processing systems. This role is critical for AI-driven healthcare solutions while ensuring high performance, accuracy, and compliance with healthcare standards.

Responsibilities:

Machine Learning & Deep Learning Development

Design and implement machine learning algorithms for healthcare AI applications.
Build and optimize deep learning models to enhance AI-driven decision-making processes.

LLM Fine-Tuning & Training

Develop and fine-tune and train large and small language models to meet domain-specific requirements.
Design robust data preparation and training pipelines for efficient model performance.

LLM Architecture Expertise

Work with state-of-the-art LLM architectures such as Transformers, GPT models, LLaMA, and others
Research and implement novel enhancements to existing language models for better contextual understanding.

Speech & NLP Project Execution

Implement speech-to-text and text-to-speech models for healthcare applications.
Develop NLP solutions for intent prediction, sentiment analysis, and medical language translation.

Programming & Development

Write and maintain high-performance Python code for ML/NLP applications.
Utilize frameworks like PyTorch and TensorFlow to train and deploy AI models.

Additional Contributions (Optional But Preferred)

Apply advanced prompt engineering techniques for optimizing LLM interactions.
Deploy ML models on cloud platforms (AWS, GCP, Azure) for scalability.
Implement MLOps best practices, including CI/CD pipelines for ML and model monitoring.

Skills and Experience:

Machine Learning & Deep Learning: Strong experience in designing, training, and deploying ML/DL models.
LLM Expertise: Hands-on experience in fine-tuning and optimizing LLMs.
NLP & Speech Processing: Experience in developing NLP solutions and speech models.
Programming: Advanced Python skills with proficiency in PyTorch and TensorFlow.
LLM Architecture: Deep Knowledge of modern transformer-based models.
MLOps & Cloud: Demonstrated experience with cloud deployment, CI/CD for ML, and model monitoring.

Qualifications:

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
3+ years of experience in ML, NLP, or AI-driven model development.
Proven track record of deploying LLM-based solutions in real-world applications.
Experience working in healthcare AI, health tech startups, or regulated industries is a plus.
Relevant certifications preferred (e.g., Google Professional ML Engineer, AWS Certified Machine Learning – Specialty).
Candidates located in Bangalore is a plus
Candidates from top universities is a plus