- Minimum 4 years experience in C++ and Linux

- Experience in IPC, Socket programming and Kernels

- Experience from a product company a must (either past or current)

Role Overview :

This role focuses on designing, developing, and optimizing distributed, high-throughput software systems operating on advanced HPC infrastructure. The position requires strong technical ownership, hands-on Linux C++ development skills, deep performance engineering experience and collaboration across multidisciplinary teams.

Key Responsibilities :

- Design and develop high-performance distributed software systems for large-scale HPC environments.

- Build and optimize Linux C/C++ components for compute-intensive and timing-critical workloads.

- Implement parallel/distributed computing frameworks using MPI, OpenMP, UCX or similar technologies.

- Containerize and orchestrate compute workloads using Docker/Singularity with Kubernetes or SLURM.

- Profile, debug, and tune system performance using VTune, Nsight, perf, gdb, and related tools.

- Drive architectural discussions, code quality, and engineering best practices.

- Collaborate with algorithms, hardware, and systems teams to deliver tightly integrated solutions.

- Mentor team members in HPC concepts, system debugging, and performance optimization.

Required Qualifications :

- Strong hands-on expertise in C/C++ development on Linux, including systems-level programming.

- Proven experience building or optimizing HPC or distributed computing systems.

- Solid understanding of concurrency, multi-threading, networking, IPC, and Linux OS internals.

- Experience with profiling/debugging tools such as VTune, Nsight, perf, ftrace, gdb.

- Experience with Docker/Singularity and orchestration frameworks (Kubernetes, SLURM).

- Knowledge of CPU/GPU architectures, high-bandwidth interconnects, and distributed storage systems.

Preferred Qualifications :

- Experience using or optimizing MPI, OpenMP, UCX, SHMEM, or similar parallel programming models.

- Exposure to GPU compute frameworks (CUDA/RoC) or GPU-aware communication libraries.

- Familiarity with deep learning or ML pipeline workflows.

- Proficiency in Python and Bash scripting.

- Background in distributed microservices, observability tools, or large-scale system deployments.

Education & Experience :

- Bachelor's or Master's degree.

- Typically 6+ years of hands-on experience in HPC, Linux systems programming or distributed systems development.