Senior C++ Systems Engineer – Linux/HPC

Location: Chennai, India

Work Type: Full-Time

Experience Required: 4 – 8 Years

About The Client

We are hiring on behalf of our client, a leading global technology company specializing in semiconductor manufacturing, inspection systems, and advanced engineering solutions.

Job Overview

Hiring a Software Engineer to build and optimize high-performance distributed systems on Linux using C++. Focus on HPC frameworks, scalability, and performance tuning across CPU/GPU environments.

Key Responsibilities
• Design and develop high-performance distributed software systems for HPC environments
• Build and optimize Linux-based C/C++ components for compute-intensive workloads
• Implement parallel computing frameworks using MPI, OpenMP, UCX, or similar
• Containerize and orchestrate workloads using Docker/Singularity with Kubernetes or SLURM
• Profile, debug, and tune performance using tools like VTune, Nsight, perf, and gdb
• Collaborate with hardware, algorithms, and systems teams for integrated solutions
• Drive code quality, architecture discussions, and engineering best practices
• Mentor team members on performance optimization and system debugging

Must-Have & Preferred Qualifications
• 4–8 years of experience in software development (HPC / distributed systems preferred)
• Minimum 4 years of hands-on experience in C++ and Linux development
• Strong understanding of IPC, socket programming, and Linux kernel concepts
• Experience in multi-threading, concurrency, and systems-level programming
• Hands-on experience with performance profiling and debugging tools (VTune, Nsight, perf, gdb)
• Experience with Docker/Singularity and orchestration frameworks (Kubernetes/SLURM)
• Knowledge of CPU/GPU architectures and distributed computing systems
• Experience with MPI, OpenMP, UCX, SHMEM, or similar parallel programming models
• Exposure to GPU computing (CUDA / ROCm)
• Familiarity with ML/Deep Learning pipelines
• Proficiency in Python and Bash scripting
• Experience with microservices, observability tools, or large-scale deployments