Jobs · Engineering · California

Senior DL Algorithms Engineer - Inference Performance

NVIDIA · Santa Clara, CA · 1 wk ago
EngineeringFull-time

About the role

NVIDIA is seeking senior engineers to optimize deep learning workloads. This role involves working across the hardware and software stack to achieve peak performance.

Responsibilities

  • Implement language and multimodal model inference as part of NVIDIA Inference Microservices (NIMs).
  • Contribute new features, fix bugs, and deliver production code to TRT-LLM, NVIDIA's open-source inference serving library.
  • Profile and analyze bottlenecks across the full inference stack to push the boundaries of inference performance.
  • Benchmark state-of-the-art offerings in various DL models inference and perform competitive analysis for NVIDIA SW/HW stack.
  • Collaborate with other SW/HW co-design teams to enable the creation of the next generation of AI-powered services.

Requirements

  • PhD in CS, EE or CSEE or equivalent experience.
  • 5+ years of experience.
  • Strong background in deep learning and neural networks, in particular inference.
  • Experience with performance profiling, analysis, and optimization, especially for GPU-based applications.
  • Proficient in C++, PyTorch or equivalent frameworks.
  • Deep understanding of computer architecture, and familiarity with the fundamentals of GPU architecture.

Qualifications

Proven experience with processor and system-level performance optimization.

Strong fundamentals in algorithms.

GPU programming experience (CUDA or OpenCL) is a plus.

Benefits

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Pay

The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

Schedule

Not specified.

Skills

Proven experience with processor and system-level performance optimization.

Strong fundamentals in algorithms.

GPU programming experience (CUDA or OpenCL) is a plus.

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