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Salary
≈ $19k – $44k per year (Estimated)
Location
In office (Pune)
Seniority
Staff · 7+ years exp

First seen by Alion on Oct 21, 2026.

Overview
Company
Impact
Profile match
Optimize AI performance with TensorMem.AI's solutions for memory optimization and GPU utilization.

Responsibilities:

  • Architecting and Execution: Leading the design, development, and delivery of low- latency, high-bandwidth distributed storage subsystems optimised to support high- scale AI workloads.
  • Distributed Subsystems: Designing, implementing, and optimising cache synchronisation mechanisms, metadata synchronisation, and distributed consistency protocols across cluster environments.
  • Low-Level Development: Writing, architecting, and debugging robust system-level software in C/C++ to build scalable distributed filesystems and object stores.
  • Hardware and Kernel Optimisation: Applying deep knowledge of computer architecture and Linux kernel design to optimise system throughput, minimise latency, and maximise hardware utilisation.
  • Integration and Standards: Driving technical integration for multi-tier distributed storage solutions (file, block, and object storage) while helping define subsystem engineering standards.
  • AI Tooling Adoption: Championing the adoption of modern AI-assisted development tools (e. g., GitHub Copilot, integrated IDE features) to maximise software quality and development velocity across the team.
  • Technical Leadership and Mentorship: Mentoring senior and mid-level engineers, leading technical design reviews, conducting rigorous peer code reviews, and guiding the team through complex system-level debugging and trade-off analysis.


Requirements:

  • Bachelor's, Master's, or PhD degree in Computer Engineering, Computer Science, Electrical Engineering, or a related technical field.
  • 7 to 10 years of hands-on professional experience in low-level systems engineering, distributed systems architecture, or high-performance computing.
  • Proven track record of designing, building, scaling, and deploying production-grade distributed storage systems.


Technical Skills:

  • Deep expertise in Computer Science fundamentals, operating systems, data structures, algorithms, and hardware architecture.
  • Advanced knowledge of metadata synchronisation, cache coherence, and consensus/consistency protocols (e. g., Paxos, Raft, lease management) in distributed environments.
  • Strong expertise in Linux kernel design principles, specifically for I/O and networking subsystems, NUMA architectures, and PCIe topologies.
  • Expert-level proficiency in C or C++ for low-level systems software development.
  • High proficiency in Python, Go, or Linux scripting for automated testing, system tooling, and performance analysis.
  • Extensive knowledge of distributed and cloud-scale storage architectures and protocols (e. g., Ceph, Lustre, NFSv4, S3, RDMA / NVMe-oF).
  • Mastery of modern development toolchains and AI-assisted coding technologies (e. g., VSCode, GitHub Copilot).
  • Deep experience with white-box profiling, performance diagnostics, and system tools (e. g., SystemTap, Valgrind, GDB, or advanced compiler flags).

Skills

C, C++, Ceph, Linux, Lustre, S3, distributed, kernel, storage

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