Staff Software Engineer (Deep Learning Acceleration)

TL;DR

Staff Software Engineer (Deep Learning Acceleration): Enhancing the performance of deep learning networks for autonomous vehicle systems with an accent on performance analysis and optimization for onboard and data center environments. Focus on reducing GPU memory usage, minimizing latency, and maximizing throughput using profiling and roofline models.

Location: San Francisco, California. Hybrid: must be in office at least 3 days per week

Salary: $189,000 - $274,000

Company

hirify.global is developing the hirify.global Driver to create a safer, more efficient, and more accessible future for mobility and logistics through self-driving technology.

What you will do

• Conduct performance analysis and optimization of Deep Learning networks running on Autonomous Vehicles.
• Optimize software architecture, system performance, and latency for deep learning applications.
• Manage the deployment of deep learning models on AVs and training on large-scale data centers.
• Troubleshoot performance bottlenecks using profiling and roofline model techniques.
• Collaborate with cross-functional teams to enhance the efficiency and reliability of self-driving technology.

Requirements

• Minimum 5+ years of professional experience in software engineering.
• BS, MS, or PhD in Computer Science or a related field.
• Strong programming skills in CUDA, C++, and Python.
• Extensive experience in high-performance computing and parallel programming for GPU optimization.
• Proficiency with NVIDIA Nsight Systems, Nsight Compute, and roofline model techniques.
• Hands-on experience optimizing DL/ML workloads using PyTorch or TensorFlow.

Nice to have

• Experience in motion planning, robotics, autonomous systems, or computer vision.
• Experience with TensorRT, OpenAI Triton, or Mojo.

Culture & Benefits

• Hybrid work environment requiring office presence at least 3 days per week.
• Collaborative culture based on integrity and ambitious goals.
• Competitive compensation including base salary, annual bonus, and equity.
• Strong organizational commitment to safety and inclusion.