Backend/Platform Engineering:

Software Engineer where I focused on: partnering with our Astrophysics team to develop algorithms for satellite collision detection/avoidance; working with the product team to build customer-facing APIs; and everything in between from building micro-services for our various internal/external tools, managing databases, and deploying said services to scale.

Explored, prototyped, and validated methodologies for hardware acceleration techniques for machine learning and 2D visual recognition applied to mobile devices (microcontrollers, self driving cars) by balancing processing, storage, and training requirements.

Met fast-paced publication deadlines by partnering with Ph.D. students to design neural networks to solve complex problems in image recognition for embedded system applications.

Optimized data processing for training/testing through GPU acceleration.

Assisted graduate-level course on machine learning fundamentals

Provided lectures on key machine learning topics, such as backpropagation, and popular deep learning frameworks, such as TensorFlow.