Senior Quantitative Research Engineer – Large-Scale HPC

1 day ago

Kottayam, Kerala, India beBeeHighPerformanceComputing Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Quantitative Research Engineer

We are seeking an experienced Quantitative Research Engineer to join our team. The successful candidate will be responsible for designing, scaling, and automating large-scale high-performance computing (HPC) platforms used in quantitative finance and research environments.

The ideal candidate will have a strong background in Linux engineering, deployment, and management of distributed file systems, HPC environments, and cloud-native infrastructure. They should also have expertise in scripting languages such as Python and Shell, as well as knowledge of AI/ML HPC offerings on cloud platforms.

  • Key Responsibilities:
  • Design and manage quant research platforms and HPC environments.
  • Research and experiment with new centralized multi-tenant clustered platforms.
  • Troubleshoot complex issues across storage, OS, and networking layers.
  • Build tools to improve performance, monitoring, and automation of HPC clusters.
  • Drive efficiency through automation of provisioning and housekeeping.
Requirements:
  • 5+ years of engineering, deployment, and management of large-scale (250+ servers) Linux infrastructure, ideally in financial services or HPC environments.
  • Expertise in distributed file systems (Lustre, GPFS) and a variety of filesystems (ZFS, XFS, ext4).
  • Strong knowledge of Linux (RHEL/CentOS/Ubuntu) configuration, troubleshooting, and performance tuning.
  • Familiarity with x86/AMD platforms optimized for both transaction speed and distributed parallel processing.
  • Networking knowledge: 10GE/25GE, InfiniBand, RoCE, RDMA.
  • Experience with Linux software RAID, hardware RAID, erasure encoding.
  • Infrastructure automation skills: Terraform, Ansible, Puppet, Chef.
  • Scripting: Python and Shell.
  • Protocol knowledge: NFS (v4.1), CIFS, SMB, ACLs.
  • Hybrid and cloud-native HPC deployment experience (AWS preferred).
  • Familiarity with AWS storage services (S3, Storage Gateway, EBS).
  • Knowledge of AI/ML HPC offerings on cloud platforms (AWS/GCP).
  • Experience with HPC job schedulers (Slurm, Condor, Airflow, SGE).
  • Hardware familiarity: HPE, Dell, Supermicro systems.
  • Commitment to the highest standards of engineering and operational excellence.
Why This Role Stands Out:
  • You'll architect, engineer, and automate large-scale HPC platforms used for quantitative finance and advanced research.
  • Work on mission-critical systems enabling portfolio managers and researchers to test and run complex models.
  • Exposure to cutting-edge HPC, cloud, and AI/ML workloads at scale.
  • Collaborate in a fast-paced, innovation-driven environment where infrastructure is seen as a strategic enabler, not a back-office function.

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