Software Engineer (AI)

Location: San Mateo, United States

Salary: $175,000–$220,000 per year, plus equity

Company

hirify.global provides an AI platform for building, training, and serving specialized models across text, image, embedding, audio, and multimodal workloads.

What you will do

• Optimize system and GPU performance for high-throughput AI training and inference workloads.
• Profile and resolve GPU-, kernel-, latency-, throughput-, memory-, and compute-efficiency bottlenecks.
• Implement low-level optimizations with CUDA, Triton, PyTorch, and related performance tooling.
• Scale LLM, VLM, and video-model systems across multi-GPU and multi-node environments.
• Build benchmarking, monitoring, and performance-configuration infrastructure.
• Collaborate with ML researchers and infrastructure teams on hardware-efficient model architectures, runtimes, and distributed systems.

Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience.
• 5+ years of experience in performance optimization or high-performance computing systems.
• Proficiency in CUDA or ROCm and experience with GPU profiling tools such as Nsight, nvprof, or CUPTI.
• Familiarity with PyTorch and performance-critical model execution.
• Experience debugging and optimizing distributed systems in multi-GPU environments.
• Deep understanding of GPU architecture, parallel programming models, and compute kernels.

Nice to have

• Master’s or PhD in Computer Science, Electrical Engineering, or a related field.
• Experience optimizing LLM, VLM, or video models for training and inference.
• Knowledge of ML compiler stacks such as torch.compile, Triton, or XLA.
• Open-source contributions to ML or HPC infrastructure.
• Experience with cloud-scale AI infrastructure, Kubernetes, or hardware-aware model design.

Culture & Benefits

• Work on low-latency inference, scalable model serving, and production AI infrastructure.
• Collaborate with engineers and AI researchers on advanced generative AI systems.
• High ownership and direct impact on system speed, scalability, and cost efficiency.
• Equity is included in the compensation package.