Experience
My professional journey in development and research
Full Stack Engineer
Invene
Lead full-stack engineer developing AI-powered clinical platforms using FastAPI, React, and PostgreSQL. Integrated advanced LLM capabilities and real-time data processing systems while maintaining high performance and compliance standards.
Key Achievements:
- Led development of clinical platforms that incorporated AI/ML components for decision support and automation
- Designed and maintained full-stack systems using FastAPI, React, and PostgreSQL, ensuring performance and compliance
- Collaborated with ML engineers to integrate LLM APIs (e.g., GPT-4, Claude) for features like summarization and data extraction
- Deployed real-time data processing pipelines for EEG analysis, integrating ONNX models
- Built semantic search capabilities using FAISS and Pinecone to power LLM-based retrieval systems
Full Stack Engineer
Axxess Technology Solutions
Full-stack engineer focused on developing healthcare applications using Django and FastAPI. Implemented NLP features and ML model deployments while optimizing frontend performance with React.
Key Achievements:
- Built scalable backend systems using Django and FastAPI for home health applications
- Integrated NLP-based extraction features into APIs for document processing and risk detection
- Worked closely with data science teams to bring ML models into production, including BERT variants for classification
- Contributed to React-based frontend modules and optimized data exchange across client interfaces
- Implemented monitoring and logging systems to support AI feature performance in real-time settings
Software Engineer
Iodine Software
Backend engineer specializing in healthcare API development and ML model deployment. Enhanced system performance and integration with EMR systems while supporting NLP and predictive modeling initiatives.
Key Achievements:
- Developed backend APIs and services to support machine learning predictions in healthcare workflows
- Integrated outputs from NLP pipelines into clinical applications via FHIR APIs
- Supported model deployment and inference tasks with Flask microservices and messaging queues
- Improved backend infrastructure performance, scalability, and EMR system integration
- Collaborated with researchers to support text mining and predictive modeling with structured outputs
Data Science Intern
Regional Healthcare Analytics Firm
Contributed to healthcare analytics projects focusing on predictive modeling and data pipeline development. Assisted in creating and validating risk stratification tools for hospital partners.
Key Achievements:
- Supported development of predictive dashboards for hospital partners
- Created data pipelines for clinical time-series datasets and applied statistical modeling
- Collaborated on early-stage risk stratification tools and helped validate predictive features