Senior Quantitative Research Infrastructure Specialist

1 week ago


Udaipur, Rajasthan, India beBeeLinux Full time ₹ 20,00,000 - ₹ 25,00,000
Quantitative Research Engineer Position

We are seeking a highly skilled Quantitative Research Engineer to join our global technology infrastructure team.

  • This role involves designing and managing advanced quant research platforms and high-performance computing environments.
  • Responsibilities also include researching and experimenting with new centralized multi-tenant clustered platforms, troubleshooting complex issues across storage, OS, and networking layers, and building tools to improve performance, monitoring, and automation of HPC clusters.

Key Responsibilities:

  • Designing and implementing large-scale Linux infrastructure for quantitative research and trading teams.
  • Managing and optimizing HPC environments to drive complex financial models, analytics, and portfolio strategies.
  • Developing and maintaining high-performance computing clusters for AI/ML applications.
  • Ensuring the highest standards of engineering and operational excellence in all projects.

Requirements:

  • 5+ years of experience in engineering, deployment, and management of large-scale (250+ servers) Linux infrastructure, preferably in financial services or HPC environments.
  • Expertise in distributed file systems (Lustre, GPFS) and various 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.

Preferred Qualifications:

  • Hybrid and cloud-native HPC deployment experience.
  • Familiarity with AWS storage services.
  • Knowledge of AI/ML HPC offerings on cloud platforms.

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