Machine Learning Engineer II

CUDAx365 black-hole simulations and Neural Radiance Field experiments for dynamic flow analysis, MHD graph kernels, and approximation studies.

I will be adding Wireshark PCAP signal usage and the electromagnetic spectrum in enclosed environments to simulate cyber attacks.

A U-Net-style segmentation pipeline adapted from 2D slices to volumetric CT data by using 3D feature blocks, skip-connected encoder-decoder paths, and spatial context across neighboring slices.

Fundus disease classification across 40 abnormality labels using fine-tuned pretrained CNNs. EfficientNet B1 was the strongest single-model choice, with high precision/recall on the reported split and a practical path toward computer-aided retinal screening.

Implementation of the World Models agent pattern: a CNN-VAE compresses image frames, an MDN-RNN predicts future latent states, and CMA-ES optimizes a compact controller over the learned latent memory.

An AR insurance prototype for inspecting policy objects and claim context in-place. The same flow can evolve with AI-assisted damage detection, guided evidence capture, and real-time claim triage.