Build, deploy, and maintain applications on HPC clusters and distributed computing environments using workload schedulers (e.g., Slurm, LSF, PBS) to support parallel computing and compute-intensive workloads
Architect and implement containerized solutions using Docker and Kubernetes for scalable distributed execution
Develop and optimize software on Linux-based systems, including performance tuning, debugging, and system-level troubleshooting
Contribute to system design, code reviews, and architectural decisions across distributed systems
Profile and improve performance, scalability, and resource utilization of HPC applications
Collaborate with cross-functional teams (DevOps, Platform Engineering, infrastructure, and product) to deliver production-grade solutions through automated CI/CD pipelines
Qualifications
Strong software development experience in
C++ (performance-critical systems, memory management, multithreading)
Python (automation, orchestration, tooling, or data workflows)
Hands-on experience with HPC clusters, including
Job scheduling systems (e.g., Slurm, LSF, PBS)
Distributed workload execution and scaling
Experience with containerization and orchestration
Docker for building and packaging applications
Strong Linux expertise, including
Shell scripting, debugging, system-level tools (e.g., perf, gdb)
Performance tuning and troubleshooting
Experience designing or building distributed or cloud-based systems
Strong problem-solving skills and ability to work on complex systems
Preferred / Nice-to-Have Skills
Experience with JavaScript / TypeScript
Experience with Angular (preferred for UI/dashboard development)
Kubernetes for deployment, scaling, and orchestration
Familiarity with
Cloud environments (AWS, Azure, or GCP)
Networking or distributed communication (e.g., gRPC, REST APIs)
GPU computing, AI Infrastructure, ML Infrastructure, distributed training, or AI/ML workloads in HPC environments.
What We're Looking For
To help us better understand your experience, we encourage candidates to provide specific examples of how they have applied the following skills in real-world or production environments:
How you used C++ and/or Python in production systems (not just coursework)
Your direct involvement with HPC clusters (setup, usage, scaling, troubleshooting, etc.)
Concrete examples of using Docker and/or Kubernetes (e.g., deployment, orchestration, CI/CD pipelines)
Practical experience working in Linux environments (debugging, performance tuning, scripting)
(If applicable) real usage of JavaScript/TypeScript/Angular in delivered features or products
Education
Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related discipline (or equivalent experience)
Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***
Design, develop, and optimize high-performance software systems using C++ and Python for distributed and compute-intensive workloads
Build, deploy, and maintain applications on HPC clusters and distributed computing environments using workload schedulers (e.g., Slurm, LSF, PBS) to support parallel computing and compute-intensive workloads
Architect and implement containerized solutions using Docker and Kubernetes for scalable distributed execution
Develop and optimize software on Linux-based systems, including performance tuning, debugging, and system-level troubleshooting
Contribute to system design, code reviews, and architectural decisions across distributed systems
Profile and improve performance, scalability, and resource utilization of HPC applications
Collaborate with cross-functional teams (DevOps, Platform Engineering, infrastructure, and product) to deliver production-grade solutions through automated CI/CD pipelines
Strong software development experience in
C++ (performance-critical systems, memory management, multithreading)
Python (automation, orchestration, tooling, or data workflows)
Hands-on experience with HPC clusters, including
Job scheduling systems (e.g., Slurm, LSF, PBS)
Distributed workload execution and scaling
Experience with containerization and orchestration
Docker for building and packaging applications
Strong Linux expertise, including
Shell scripting, debugging, system-level tools (e.g., perf, gdb)
Performance tuning and troubleshooting
Experience designing or building distributed or cloud-based systems
Strong problem-solving skills and ability to work on complex systems
Preferred / Nice-to-Have Skills
Experience with JavaScript / TypeScript
Experience with Angular (preferred for UI/dashboard development)
Kubernetes for deployment, scaling, and orchestration
Familiarity with
Cloud environments (AWS, Azure, or GCP)
Networking or distributed communication (e.g., gRPC, REST APIs)
GPU computing, AI Infrastructure, ML Infrastructure, distributed training, or AI/ML workloads in HPC environments.
What We're Looking For
To help us better understand your experience, we encourage candidates to provide specific examples of how they have applied the following skills in real-world or production environments:
How you used C++ and/or Python in production systems (not just coursework)
Your direct involvement with HPC clusters (setup, usage, scaling, troubleshooting, etc.)
Concrete examples of using Docker and/or Kubernetes (e.g., deployment, orchestration, CI/CD pipelines)
Practical experience working in Linux environments (debugging, performance tuning, scripting)
(If applicable) real usage of JavaScript/TypeScript/Angular in delivered features or products
Education
Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related discipline (or equivalent experience)
Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***
