Senior System Software Engineer, Computer Vision Performance

Posted 12 Days Ago
Be an Early Applicant
Santa Clara, CA
Expert/Leader
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
The role involves optimizing performance of core computer vision SDKs and services, focusing on data-center and edge workloads. Responsibilities include profiling, debugging, improving algorithms using CUDA, defining performance metrics, and collaborating with different teams for high-performance computing solutions.
Summary Generated by Built In

NVIDIA is a world-leader in high speed computer vision, artificial intelligence, and deep learning. Our team builds and optimizes computer vision AI models, SDKs, and cloud services to bring real-time hardware-accelerated AI to data centers, gaming rigs, cars, robots, buildings, medical devices, and more.

We are now looking for an expert in system-level software optimization to own the performance of our core computer vision SDKs and services. The right candidate will bring insight into challenges of delivering performance at scale and passion for multi-disciplinary teamwork and efficient, well-crafted software.

What you'll be doing:

  • Profile, debug, and optimize data-center and edge computer vision workloads for efficiency, latency, and throughput.

  • Implement and improve computer vision and image processing algorithms using CUDA.

  • Establish and drive product-critical performance metrics.

  • Influence software architecture and technical roadmaps to ensure outstanding performance.

  • Contribute to large codebases combining custom C++ and Python with distributed architectures (microservices, Kubernetes, Triton) to deliver computer vision at scale.

  • Provide technical leadership in high-performance computing to computer vision teams across NVIDIA.

What we need to see:

  • Master's of Science in Computer Science or Electrical engineering (or equivalent experience)

  • 10+ years practical experience.

  • Excellent software engineering fundamentals (source control, CI/CD, testing/validation, packaging, containerization, release). Proven track record developing, testing and releasing production-grade, complex software.

  • Proficiency with C++, CUDA, and Python.

  • Strong fundamentals with multi-threaded and distributed software development.

  • Experience with performance-critical data center applications.

  • Proven track record defining and driving performance metrics to ensure product success and differentiation.

  • Excellent written, visual, and verbal communication to present performance challenges, tradeoffs, and architectural alternatives.

  • Strong collaboration skills to partner with algorithm designers, application developers, and infrastructure and MLOps teams.

  • Ability and desire to learn new technologies.

Ways to Stand Out from the Crowd:

  • Experience with classical and machine-learning based computer vision including ML-Ops.

  • Grounding in mathematical fundamentals such as linear algebra, numerical methods, statistics, and exploratory data analysis.

  • History of creativity and innovation around performance in multiple problem domains.

#LI-Hybrid

The base salary range is 224,000 USD - 425,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Top Skills

C++
Cuda
Python
The Company
HQ: Santa Clara, CA
21,960 Employees
On-site Workplace
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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