Software Engineer

Red Hat•Boston, MA

2d•Hybrid

About The Position

Design, develop, troubleshoot and debug software programs for enhancements and new products. Develop software and tools in support of design, infrastructure and technology platforms, including operating systems, compilers, routers, networks, utilities, databases, cloud-based and Internet-related tools. Analyze the performance characteristics of AI systems on edge devices to perform capacity planning activities and to resolve system performance issues, optimize the stack for resource efficiency and strict performance / latency requirements. Enable the use of the RHEL operating system on edge devices by integrating vendor drivers into the system images, and promote system changes through an automated continuous integration / continuous delivery (CI/CD) system and use automated system monitoring software to assess its ongoing performance and operation. Collaborate with other engineers and architects to create and review software design proposals on the dimensions of feasibility, scalability, security, maintainability, and fitness to purpose, to design and implement a MLOps (machine learning operations) system suitable for use in an industrial / edge environment. Determine hardware compatibility and/or influences hardware design. Build framework and integration documentation for development teams.

Requirements

Bachelor’s degree (U.S. or foreign equivalent) in Computer Science, Computer Engineering, or related field and two (2) years of experience in the job offered or related role OR Master’s degree (U.S. or foreign equivalent) in Computer Science, Computer Engineering, or related field.
Programming in Python
Programming in Golang
Cloud Native Technologies and Platforms, including Kubernetes or Red Hat OpenShift
Contributor-level with Hardware-in-the-Loop (HIL) testing
Operating system level programming
Embedded systems and hardware enablement of these systems
Cryptography and cybersecurity
Computer networking
Preparing customer facing workshop materials

Responsibilities

Analyze the performance characteristics of AI systems on edge devices to perform capacity planning activities and to resolve system performance issues, optimize the stack for resource efficiency and strict performance / latency requirements.
Enable the use of the RHEL operating system on edge devices by integrating vendor drivers into the system images.
Promote system changes through an automated continuous integration / continuous delivery (CI/CD) system.
Use automated system monitoring software to assess its ongoing performance and operation.
Collaborate with other engineers and architects to create and review software design proposals on the dimensions of feasibility, scalability, security, maintainability, and fitness to purpose.
Design and implement a MLOps (machine learning operations) system suitable for use in an industrial / edge environment.
Determine hardware compatibility and/or influences hardware design.
Build framework and integration documentation for development teams.