全职 HPC(High Performance Computing) Engineer 工作, 薪水 up to SGD 9,000, Infinite Computer Solutions Pte Ltd 公司招聘中 - Ricebowl

Technical Skills:

High-Performance Computing

Hands on experience in managing HPC clusters with job scheduler, cluster management parallel programming libraries, and parallel filesystems.

Knowledge of resource scheduling and job optimization for efficient workload management

Infiniband (Networking)

Hands-on experience with high-throughput, low-latency interconnect technologies like Infiniband.

Ability to design, configure, and troubleshoot interconnects in HPC or distributed environments.

Operating Systems and Environments 

Administration and configuration of RHEL-based systems.

Performance tuning, package management, and security hardening.

Knowledge of Red Hat Satellite and Ansible for automation.

Job Scheduling with PBS Professional 

Experience in deploying and managing PBS Professional for scheduling and workload management in HPC environments.

Customizing job submission scripts and optimizing job queues.

Parallel Programming Libraries

MPI (Message Passing Interface) and OpenMP (Open Multi-Processing):

Proficiency in writing, debugging, and optimizing parallelized code.

Experience with scaling applications across HPC systems.

Understanding of distributed memory (MPI) and shared memory (OpenMP)

paradigms.

Cloud Platforms

AWS, Azure, Google Cloud:

Expertise in provisioning, configuring, and managing services on all three platforms.

Cross-platform migration and hybrid cloud solutions knowledge.

Proficiency in managing high-performance computing (HPC) clusters on the cloud.

Deep understanding of cost optimization, security, and cloud native development tools (e.g., Kubernetes, Terraform).

Infrastructure as Code (IaC) 

Ability to design, deploy, and maintain infrastructure using automation and configuration management tools.

CI/CD pipeline integration for IaC workflows.

GPU & AI Libraries and Tools 

Hands-on experience with container technologies.

Hands-on experience with TensorFlow, PyTorch, scikit-learn, Keras, or MXNet.

Familiarity with AI/ML pipelines, model training, and optimization.

Knowledge of MLOps tools for deploying and monitoring models