Dharmendar Reddy Palle — Machine Learning Engineer

I have 15+ years experience in developing high performance parallel codes in C++/Fortran. Deployed codes in large distributed systems and resource constrained edge devices. Working experience of numerical packages (such as PETSc, Trillionos, Intel MKL etc), Deep learning frameworks (PyTorch, TensorFlow) and inference runtimes (onnxruntime and OpenVINO). Experience in deploying codes to Jetson Nano echo system, Intel VPU chips. 1. Tech lead for implementation AI-powered active speaker detection and multiple video stream generation for Intelligent camera for Teams (https://bit.ly/3JxKkj2) 2. Experienced in End-to-End Machine learning flow with audio/visual data. 3. Model optimization and deployment for realtime audio/video inference in resource constrained devices. Additionally, I also have strong back ground in Semiconductor device physics and Technology. 1. Over 6 year of experience in leading semiconductor device technology path finding for 7nm, 5nm, 3nm and beyond nodes. 2. Performed TCAD and first principles analysis of Semiconductor devices (FinFET, MBCFET etc) with commercial and in-house tools. 3. Extensively worked in HPC cluster environment with large parallel codes such as NEMO. 4. Skilled in Device simulation, Circuit simulation, Classical and Quantum electron transport, Research Management etc. Technical Skills: • Device/Circuit Simulators: Cadence Spectre, HSPICE, Synopsys TCAD (device/process) simulation tools • Mathematical Tools: MATLAB/Octave, Mathematica, R, numerical libraries (PETSc, Trillinos, MKL etc) • Core Programming: C++/C/C#, Python, FORTRAN, MPI/OpenMP, TCL, Scheme • Data Science/ML: Pytorch, caffe/caffe2, Tensorflow, scikit-learn ,SQL • Web/App development: HTML5, CSS3, JavaScript, familiarity with AngularJS/ReactJS, .Net UWP • Development Tools: Linux scripting/build tools, version control (git, svn etc), debug/profiling, LSF/UGE/SLURM

Stackforce AI infers this person is a Semiconductor and Machine Learning expert with extensive experience in high-performance computing.

Location: Seattle, Washington, United States

Experience: 12 yrs 10 mos