AI Scientist

We are looking for an AI Scientist to build and scale the next generation of AI-driven 

healthcare solutions. In this role, you will be a key contributor to our Healthcare 

Information System (HIS) applications, moving beyond experimental notebooks to build 

real-world, secure, and scalable AI/ML applications.

You will work across the full spectrum of AI—from Classical ML and Deep Learning to 

exploring Generative and Agentic AI—ensuring our tools are reliable and transformative 

for clinicians and patients

Key Responsibilities

1. Model Development & Deployment

• Build & Iterate: Design, train, and fine-tune ML models using a mix of classical 

statistical methods and modern deep learning architectures.

• Full-Cycle Execution: Assist in the end-to-end process of taking models from data 

cleaning and feature engineering to deployment in production environments.

• Generative AI Integration: Implement and evaluate LLM-based components and 

agentic workflows to enhance system reasoning and natural language capabilities.

2. Data Science & Engineering

• Clinical Data Handling: Process and analyze structured and unstructured 

healthcare data (e.g., FHIR, clinical notes, claims) to extract actionable insights.

• Evaluation & Testing: Conduct rigorous testing to ensure model accuracy, fairness, 

and safety within a highly regulated healthcare context.

• Performance Tuning: Optimize models for latency and throughput to meet the 

demands of real-time healthcare applications.

3. Collaboration & Growth

• Technical Partnership: Work independently or closely with other scientists and 

engineers to translate research requirements into production-ready code.

• Documentation: Maintain clear documentation of experiments, model 

architectures, and data pipelines to ensure reproducibility

Candidate Profile

Education & Experience:

• Master’s in Computer Science, AI, Machine Learning, or a related field (or a 

Bachelor’s with 5+ years of relevant industry experience).

• Hands-on Experience: At 3+ years of experience developing and deploying AI/ML 

models in a professional or intensive academic setting.

Core Technical Stack:

• ML Fundamentals: Solid foundation in Classical ML (Regression, Clustering, Treebased models) and Deep Learning (Neural Networks, Transformers).

• GenAI Awareness: Experience with (or strong interest in) Generative AI

frameworks, RAG systems, and prompt engineering.

• Programming: Proficiency in Python and standard ML libraries (PyTorch, 

TensorFlow, Scikit-learn, Hugging Face).

Bonus Points (Preferred):

• MLE/MLOps: Familiarity with Git, Docker, or basic MLOps workflows.

• Cloud Basics: Exposure to cloud platforms like AWS, GCP or Azure.

• Healthcare Focus: Understanding of medical data privacy (HIPAA) or healthcare 

data formats