Engr, Software 1

KLA•Ann Arbor, MI

1d•Onsite

About The Position

In this role, you will play a key part in advancing business priorities by delivering high-impact work across your area of expertise. Engineers in the Software team will be working on building and maintaining infrastructure vital for large scale experimentation and deployment of HPC solutions. Domains in which a successful candidate will be encouraged to chip in, will include, data management and data loading, support for machine learning and deep learning model training. Although familiarity with Machine Learning and Deep Learning solutions would be a huge plus, this is primarily a Software Engineering position. Successful candidates are passionate about software and will have outstanding skills and hands on experience with development in C/C++ and Python in a Windows/Linux environment. Deep conceptual understanding of multi-threaded, multi process and distributed software systems is vital.

Requirements

Outstanding skills and hands on experience with development in C/C++ and Python in a Windows/Linux environment.
Deep conceptual understanding of multi-threaded, multi process and distributed software systems is vital.
Object Oriented Design & Programming in Java or C++
Scripting languages like Java Script, Python
Data Structures and algorithms
Linux System Programming
Distributed systems
BS in Math, CS, Engineering or related field.
Bachelor's Level Degree and 0 years related work experience

Nice To Haves

Familiarity with Machine Learning and Deep Learning solutions
Cloud technologies for network, storage, containerization and compute clusters.
Building and configuring Linux kernels, and designing and fixing network infrastructure.
Linux Device Driver Development
Understanding of various networking stacks
GPU Architectures and CUDA (CuGraph, CuData, CuML etc).
Distributing computing frameworks like Apache Spark, DASK

Responsibilities

Building and maintaining infrastructure vital for large scale experimentation and deployment of HPC solutions.
Data management and data loading.
Support for machine learning and deep learning model training.
Creating the techniques and methods to integrate multiple hardware and software subsystems to seek sophisticated technical challenges.
Data science skills to acquire, transform and present data from various sources to build powerful debugging and analysis software.