I am an engineer with 9 years experience working in "Silicon Valley". I have a genuine passion for figuring things out. I started my career in technology as a Hardware Engineer, but for the past two years I have been working as a Software Engineer in the Machine Learning space. My focus has been on accelerating inference for convolutional neural networks on FPGAs.

Machine Learning   Caffe   TensorFlow   CNN   LSTM   MLP   Python   C++   JavaScript   HTML   REST   Caffe   Microservices   API Design   git   gdb / pdb debugging   docker   Verilog   SystemVerilog   Xilinx FPGA Architecture   PCIe   Ethernet  

Python: My current role uses Python as the primary language and I have been building applications in Python for the past two years. I am familiar with a range of Python packages, such as Numpy and Flask, as well as familiarity with a range of Machine Learning frameworks.

C++: My current role uses C++ for developing optimized lower level libraries for accelerating Inference.

Verilog I have used Verilog for logic design and verification/simulation. I primarly used this language for developing chips in the telecommunications space.

Cloud platforms: I have primarily used AWS for running production apps on the cloud. I have experience setting up, configuring, and running applications using a range of AWS offerings, including EC2, ELB, Route53, and S3.

Web Development: Through building web applications, I have also worked with various client side technology, having used jQuery, Bootstrap, and Electron. This is not my primary area of work, but through building demos I've gotten more and more experienced here.

Development Control: I have a good knowledge of application life-cycle management and have worked with SVN, Git, Jenkins, etc. I have experience with an array of testing tools, scripting languages, and technologies.