
Junior AI Developer with hands-on experience in designing and implementing AI-driven solutions for real-world applications. Skilled in building and optimizing computer vision models for damage detection and condition prediction. Proficient in real-time data processing, model evaluation, and performance tuning using Python and YOLO frameworks. Experienced in collaborating on API integrations with .NET teams to automate and enhance report generation workflows. Passionate about leveraging AI to improve efficiency, accuracy, and automation in business processes.
Programming Languages: Python, SQL, C#, JavaScript (basic)
Machine Learning & NLP: Scikit-learn, SpaCy, NLTK, Transformers (Hugging Face), SentenceTransformers, OpenAI API, LangChain
Deep Learning Frameworks: PyTorch, TensorFlow, Keras
Embeddings & Vector Search: FAISS, Pinecone, ChromaDB, OpenAI Embeddings, Similarity Search
Data Processing & Analytics: Pandas, NumPy, Matplotlib, Seaborn, Data Cleaning & Preprocessing
Entity Extraction & Ontology Mapping: Named Entity Recognition (NER), RxNorm, SNOMED-CT, ICD-10, MeSH (familiarity with medical data pipelines)
Risk Triage & Classification: Confidence Scoring, Rule-Based Classification, Clustering (K-Means, DBSCAN, Hierarchical), Anomaly Detection
Model Serving & APIs: FastAPI, Flask, RESTful API Development, JSON Data Handling
Prompt Engineering & LLM Integration: Prompt Tuning, Chain-of-Thought Pipelines, Template-based Script Generation (using GPT Models)
Evaluation & Metrics: Precision, Recall, F1-Score, Calibration, A/B Testing
MLOps & Deployment: Docker, Git, Model Versioning, MLflow, CI/CD, Drift Monitoring
Databases & Storage: PostgreSQL, MongoDB, Vector Databases, ElasticSearch
Cloud & Tools: AWS S3/EC2, Azure ML, Google Cloud AI, Jupyter, VS Code, GitHub