Machine Learning Engineer

AI/ML Development San Jose, California, United States

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Summary

Developed FDA-approved deep learning models for tissue differentiation in surgical procedures, including live surgery
participation.
Implemented PyTorch-based U-Net model for needle tracking in breast biopsy, achieving real-time performance at 45fps.
Optimized algorithm performance by transitioning CPU-based operations to GPU using CUDA and OpenCV tools.
Enhanced software performance by 20% through the creation of dynamic libraries in C++.
Conducted research and implementation of beamforming techniques in ultrasound data involving DSP techniques.
Established server-client communication for ultrasound image transfer using grpc and ROS2.
Deployed Remote Desktop Protocol on AWS EC2 instance for running multiple software instances.

Expectations

I am looking for a job where I can grow professionally. It would be great if I get to work on cloud. I want to work at a place where I can work on my own but also get proper mentoring whenever needed. I like to work at a place where my work is appreciated and I can see I am having a positive impact on the company and company's vision.