Parallel Processing Engineer

At Crossing Hurdles, we work as a referral partner. We refer candidates to our partner that collaborates with worlds leading AI research labs to build and train cutting-edge AI models.

Position: Parallel Processing Engineer

Type: Hourly Contract

Compensation: $10.5 per hour

Location: India (Remote)

Commitment: Part-time (20-30 hours/week), flexible

Role Responsibilities:

• Accelerate numeric and simulation kernels using GPU/CPU parallelism.
• Optimize workloads through memory-hierarchy tuning and communication reduction strategies.
• Scale large computational workflows across distributed clusters using MPI, NCCL, and Slurm.
• Profile, benchmark, and tune performance using tools like nvprof and nsys.
• Build reproducible HPC pipelines using Python, NumPy, and SciPy.
• Integrate parallel computing optimizations into production AI and scientific systems.
• Collaborate with researchers and engineers to enhance performance across large-scale computational workloads.

Requirements:

• Background in computer science, high-performance computing, or applied mathematics.
• Hands-on experience with GPU/CPU parallel programming (CUDA, OpenMP).
• Strong understanding of distributed execution frameworks (MPI, NCCL, Slurm).
• Proficiency in Python with scientific computing libraries (NumPy, SciPy).
• Experience profiling and optimizing workloads using tools like nvprof and nsys.
• Strong understanding of memory hierarchy, communication overhead, and scalability constraints.
• Interest in accelerating AI training, simulations, and scientific computations through HPC techniques.

Key Domains:Applicants with strengths in the following domains are highly encouraged to apply:

• High-Performance Computing (HPC): Parallel programming, cluster execution, GPU/CPU optimization
• Distributed Systems: MPI, NCCL, Slurm, cluster scaling
• Scientific Computing: Numeric kernels, simulations, Python-based HPC workflows
• Performance Engineering: Profiling, benchmarking, memory tuning
• AI Acceleration: HPC methods for AI training and large-scale models

Application Process:

• Apply for the job role
• Await the official message/email from our recruitment team (typically within 1-2 days)