Machine Learning Engineer with over 3 years of experience specializing in optimizing model performance and tuning low-precision neural networks. Successfully improved model accuracy training speed, and accelearted data science efficiency by implementing advanced ML techniques and leveraging distributed training systems. Experienced in end-to-end ML pipeline optimization and real-time deployment for surveillance applications. Have worked with Explainable AI techniques and Exploratory Data Science in genomic research. Worked in Computer Vision field for 2 years in Intelligent Video Analytics for Smart Cities. Have done several projects in NLP, and utilizing Large Language Models (LLM) based solutions for Generative AI tasks.
Interests 👨🏻💻: Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Data Science, MLOps, Generative AI, LLM
Hobbies 🔭: playing guitar, piano, stargazing, traveling, sudoku, poetry.
Experience
Machine Learning Engineer - Autodesk
Boston, MA, US, Oct 2024 - Present
Autodesk Research: Generative AI and 3D Computer Vision
Deep Learning Research Co-op - The Jackson Laboratory
Boston, MA, US, Jul 2023 – Dec 2023
Researched and applied Explainable AI methods for Graph Neural Networks.
Technologies used: PyTorch Geometric, PyTorch Captum
Machine Learning Engineer - Vehant Technologies
Delhi, India, Jun 2019 – Aug 2022
Intelligent Video Analytics for Smart City: 2D/3D computer vision, object detection, tracking, reidentification, license plate recognition (ANPR OCR), action recognition, pose estimation, depth estimation.
MLOps: Distributed Training, Deployment, ETL, and Optimization of multi-GPU end-to-end ML pipelines (PyTorch, TensorFlow, Nvidia TensorRT, CUDA, DeepStream, MLFlow, ONNX, AWS SageMaker).
Accelerated Data Science: Low precision, Quantization, Pruning, Nvidia RAPIDS.
Mentoring: 2 fellow teammates Edge AI topics.
Computer Vision R&D Intern (continued)
Jun 2019 - Jul 2020Researched on deep-learning-based monocular depth estimation methods for under-vehicle object detection.
Technologies used: PyTorch, TensorFlow, NVIDIA DeepStream, OpenCV, MLOps
NLP Intern - Arbunize Digital Pvt. Ltd.
Delhi, India, Jun 2018 - Aug 2018
Applied Natural Language Processing algorithms on resumes for automatic information extraction and processing.
Technologies used: Python, NLTK, Keras, scikit-learn
Projects
Check the complete list on the PROJECTS page.