Senior HPC Engineer

Binaire Private Limited; New Delhi; On-site; INR 1,500,000 - 2,500,000; Full time

Benefits offered by this job

Opportunity to influence hardware selection

Ownership of high-performance compute infrastructure

Job summary

A technology infrastructure company in New Delhi is looking for a Senior HPC Engineer to design, optimize, and operate large-scale compute systems. The ideal candidate will have strong experience in C/C++ and parallel computing models, with hands-on experience in HPC clusters. Key responsibilities include developing parallel applications, profiling performance, and leading capacity planning. This role offers the chance to work on demanding compute workloads with a significant impact on infrastructure efficiency.

Qualifications

• Strong experience in C/C++ is required; Python experience is desirable.
• Deep knowledge of parallel computing and its models.
• Hands-on experience with HPC clusters and workload managers is essential.

Responsibilities

• Design and optimize HPC systems for performance, scalability, and reliability.
• Develop parallel applications using MPI, OpenMP, or CUDA.
• Lead benchmarking, capacity planning, and performance testing.

Skills

C/C++

Parallel computing models (MPI, OpenMP, CUDA)

CPU/GPU architecture knowledge

Linux systems knowledge

HPC clusters experience

Tools

Slurm

PBS

Docker

Apptainer/Singularity

Job description

We’re building compute infrastructure for high-throughput, low-latency workloads that push modern hardware to its limits. As a Senior HPC Engineer, you will design, optimize, and operate large-scale compute systems powering AI inference, simulation, and data-intensive workloads.

This role is for engineers who excel in parallel computing, performance engineering, and systems-level optimization across heterogeneous hardware.

What You’ll Do

• Design and optimize HPC systems and clusters for performance, scalability, and reliability
• Develop and tune parallel applications using MPI, OpenMP, CUDA, or hybrid models
• Optimize workloads across CPU, GPU, and accelerator-based architectures
• Profile and analyze performance bottlenecks (compute, memory, I/O, interconnect)
• Architect high-performance networking (InfiniBand, RDMA) and storage pipelines
• Improve job scheduling, resource utilization, and queue efficiency
• Lead benchmarking, capacity planning, and performance regression testing
• Build automation for cluster provisioning, monitoring, and fault recovery
• Mentor engineers and establish best practices for performance engineering
• Collaborate with ML, inference, and infra teams on cross-domain optimization

Required Skills

• Strong experience in C/C++ (required); Python for orchestration and tooling
• Deep knowledge of parallel computing models (MPI, OpenMP, CUDA)
• Strong understanding of CPU/GPU architecture, memory hierarchy, and NUMA
• Hands‑on experience with HPC clusters and workload managers (Slurm, PBS)
• Experience with high-performance networking (InfiniBand, RDMA, NCCL)
• Strong Linux systems knowledge and performance debugging skills
• Proven experience operating or optimizing production-scale HPC environments

Nice to Have

• Experience with AI/ML workloads on HPC systems
• Familiarity with GPU-direct storage, NVMe-oF, or Lustre/GPFS
• Knowledge of power, thermal, and performance tuning at rack or node level
• Experience with containerized HPC (Apptainer/Singularity, Docker)
• Contributions to HPC tooling, benchmarks, or open-source projects

What You’ll Gain

• Ownership of high-performance compute infrastructure at scale
• Direct impact on , efficiency, and infrastructure cost
• Opportunity to influence hardware selection and system architecture
• Work on some of the most demanding compute workloads in production