Parallel Computing Engineer (CUDA)

Location: 100% remote within the United States

Salary: $130,000–$180,000 annually

Company

hirify.global is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.

What you will do

• Design, develop, and optimize CUDA kernels for AI, deep learning, and scientific computing workloads.
• Profile GPU workloads with NVIDIA Nsight Systems, Nsight Compute, CUDA Profiler, and related tools.
• Optimize GPU memory management, kernel execution, occupancy, multi-GPU scaling, and distributed computing performance.
• Design distributed training and inference architectures using NCCL, MPI, CUDA-aware communication libraries, and high-performance networking.
• Develop custom GPU operators and optimized kernels for PyTorch, JAX, Triton, TensorFlow, and similar frameworks.
• Build benchmarking and performance regression pipelines, collaborate with AI and software teams, and mentor engineers.

Requirements

• 10+ years of professional experience in GPU programming, high-performance computing, or parallel computing.
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline.
• Expert proficiency in CUDA C/C++, GPU architecture, and massively parallel programming.
• Extensive experience with NCCL, MPI, CUDA-aware MPI, and distributed GPU communication frameworks.
• Experience integrating custom GPU kernels with PyTorch, TensorFlow, JAX, Triton, or similar machine learning frameworks.
• Strong C/C++ programming, debugging, profiling, analytical, collaboration, and technical leadership skills.

Nice to have

• Experience with CUTLASS, TensorRT, FasterTransformer, vLLM, DeepSpeed, or similar GPU optimization frameworks.
• Knowledge of LLVM, MLIR, compiler optimization, or code generation technologies.
• Experience with distributed AI training, model parallelism, pipeline parallelism, and inference optimization.
• Familiarity with AWS, Microsoft Azure, or Google Cloud Platform GPU infrastructure.
• Open-source contributions, research publications, patents, technical presentations, or experience with AMD ROCm and Intel accelerator technologies.

Culture & Benefits

• Full-time direct W2 employment.
• Career growth opportunities within an established consulting and software development organization.
• Work remotely within the United States.
• U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply.
• New H-1B visa petitions are not sponsored for this position.