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Experienced Senior Machine Learning Engineer with 5+ years AI/ML solution development across healthcare, robotics, eCommerce and manufacturing sectors. Has led development of non-invasive health monitoring AI, reducing patient diagnostic time by 25% and contributing to successful acquisition and IPO. Spearheaded the creation of machine learning pipelines that reduced data processing time by 40% and enhanced diagnostic accuracy to 90%. Optimised cloud deployments, cutting server costs by 35% and increasing user acquisition by 50%
Inventor of several patents and author of many research papers, recognised for innovations in computer vision, reinforcement learning and NLP. Proven track record of enhacing operational efficiency by 25% and contribution to $5m in seed funding through AI-driven solutions.
Programming: Python, MATLAB, C++, CUDA< SQL, Docker & JavaScript
ML Frameworks: TensorFlow, PyTorch, OpenCV, ONNX, NVIDIA-MONAI, Spacy, Statsmodels,Scikit-Learn, Stablebaselines3, Scipy, Cytomine API, Bio Python, LangChain, Llamalndex, Autogen, Ray, Apache Spark
ML Ops: NVIDIA Triton Inference Server, TensorRT, AWS Sagemaker, Vertex AI, Kubeflow, Compute Engine, Cloud Storage, Apache Kafka
Deep Learning Technologies: Segmentation, Object Detection, Reinforcement Learning, Casual Reasoning, Natural Language Processing, Regression Analysis, Responsible SI, AI Governance, AI Safety, BERT, GEMINI, GPT, DALL-E, AlphaFold, BARK, Falcon-13B, Llama-2, LLM (RAG Tuning, DPO)
Tools: Plotly, Tableau, ImageJ, Docker, GIT, Linux, Build-Root, Databricks, PowerBI
Education:
MSC in Applied Artificial Intelligence
BTech in Computer Scient and Biomedical Engineering
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