Siddharth Joshi
Highly skilled Machine Learning Engineer with a strong foundation in Materials Science and Engineering, as well as a minor in Computer Science. Experienced in developing AI-powered solutions, with a proven track record of high accuracy and performance. Adept at using a variety of technical tools and software to manage and analyze data.
- Role
Machine Vision Engineer
- Years of Experience
1.2 years
- Professional Portfolio
View here
Skillsets
- Instance segmentation
- HuggingFace
- Yolo
- XgBoost
- U-net
- Rest APIs
- OpenVINO
- OpenCV
- ONNX
- MySQL
- model optimization
- MLFlow
- Medical Image Analysis
- LangChain
- Keras
- JavaScript
- AWS - 1 Years
- Git
- Flask
- Edge Computing
- Distributed Training
- Linux
- HTML
- CSS
- C++
- TensorFlow
- SQL
- Scikit-learn
- PyTorch
- Python - 1 Years
- object detection
- Docker
Professional Summary
1.2Years
- Sep, 2024 - Present1 yr 3 months
Machine Vision Engineer
Neuranics Lab - Jul, 2023 - Nov, 2023 4 months
Machine Learning Engineer Intern
Sprih Labs
Applications & Tools Known
VS Code
Google Cloud Platform
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Docker
Postman
AWS
Linux
Github
Work History
1.2Years
Machine Vision Engineer
Neuranics LabSep, 2024 - Present1 yr 3 months
Leading AI/ML development for 5-minute CBC point-of-care diagnostic device, validated on 200+ clinical samples at premier medical institutions. Optimized deep learning segmentation pipeline to run under 2s on CPU and 800ms on NVIDIA Jetson Orin Nano using TensorRT, enabling real-time point-of-care diagnostics with 25x faster inference than industry baseline. Developed multi-modal image classification system using hierarchical CNNs, improving inference accuracy and deployment readiness. Built comprehensive cell detection pipeline using 3D peak detection, DBSCAN clustering, achieving less than 15% error rate. Designed automated Complete Blood Count analysis achieving greater than 95% accuracy for clinical deployment. Developed full-stack web-based classification tool using Flask and JavaScript for expert annotation with multi-doctor authentication.
Machine Learning Engineer Intern
Sprih LabsJul, 2023 - Nov, 2023 4 months
Integrated GPT-based LLMs with document parsing pipelines (Google Document AI) for automated invoice understanding, achieving 95%+ accuracy. Designed optimized MySQL database schemas with Docker containerization for scalable AWS cloud deployment. Built RESTful APIs and microservices architecture for seamless integration with existing enterprise systems.
Achievements
- Developed a Generative AI service with over 95 percent accuracy in information extraction.
- Created a deep convolutional neural network with 97 percent accuracy in predicting optical behavior of metasurfaces.
- Implemented a Differential Evolution Optimization algorithm resulting in a 43-fold reduction in optimization duration.
Major Projects
2Projects
AI-Assisted Nanophotonic Structure Discovery
Designed deep learning-assisted surrogate optimization for automated metasurface design achieving 43-fold computational speedup. Trained neural network achieving less than 5% error while reducing design iteration time from hours to minutes.
Handwritten Signature Verification using CNNs
Developed Inception-inspired CNN architecture achieving 74.65% validation accuracy on 11,280 signature image dataset. Implemented comprehensive preprocessing pipeline and data augmentation for improved model robustness.
Education
Bachelor of Technology in Materials Science and Engineering, Minor in Computer Science and Engineering
Indian Institute of Technology (IIT), Gandhinagar (2023)