Staff Software Engineer, Deep Learning Acceleration

Pittsburgh Robotics Network

Pittsburgh (Allegheny County)

On-site

USD 120,000 - 180,000

Full time

14 days+

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Benefits offered by this job

Annual bonus
Equity compensation
Benefits

Job summary

Pittsburgh Robotics Network in Pittsburgh, PA, seeks a senior software engineer to lead performance analysis and optimization of deep learning systems for autonomous vehicles.

The role focuses on optimizing architecture and latency for onboard deployment and large-scale data-center training, requiring 5+ years of software engineering experience and expertise in CUDA, C++, Python, and DL frameworks.

Qualifications

  • At least 5 years of software engineering experience.
  • Degree in Computer Science or related field.
  • Proficiency in CUDA, C++, Python and DL frameworks such as PyTorch or TensorFlow.

Responsibilities

  • Perform performance analysis and optimization of deep learning networks for autonomous vehicle systems.
  • Optimize software architecture and latency for onboard vehicle deployment and large-scale data center training.

Skills

CUDA
C++
Python
HPC
Parallel programming
NVIDIA Nsight Systems
Nsight Compute
Roofline model
PyTorch
TensorFlow
Computer vision
Transformer-based architectures
Linux/Unix
TensorRT
OpenAI Triton
Mojo

Education

Bachelor's degree in CS or related field

Job description

Requirements:

Candidates need at least 5 years of software engineering experience and a degree in Computer Science or a related field. Proficiency in CUDA, C++, Python, and deep learning frameworks like PyTorch or TensorFlow is required.

Key Skills:
  • CUDA
  • C++
  • Python
  • High-performance computing
  • Parallel programming
  • NVIDIA Nsight Systems
  • Nsight Compute
  • Roofline model
  • PyTorch
  • TensorFlow
  • Computer vision
  • Transformer-based architectures
  • Linux/Unix
  • TensorRT
  • OpenAI Triton
  • Mojo
Benefits:
  • Annual bonus
  • Equity compensation
  • Benefits

The role involves conducting performance analysis and optimization of deep learning networks for autonomous vehicle systems. You will optimize software architecture and latency for both onboard vehicle deployment and large-scale data center training.

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