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Software Engineer

Netflix - 1d ago

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Senior Software Engineer

Reddit - 4d ago

Senior Deep Learning Software Engineer, Inference

Requirements:

  • Masters or PhD or equivalent experience in relevant field (Computer Engineering, Computer Science, EECS, AI).
  • 5+ years of relevant software development experience.
  • Excellent C/C++ programming and software design skills. SW Agile skills are helpful and Python experience is a plus.
  • Prior experience with training, deploying or optimizing the inference of DL models in production is a plus.
  • Prior background with performance modeling, profiling, debug, and code optimization or architectural knowledge of CPU and GPU is a plus.

Nice to haves:

  • Experience with Multi-GPU Communications (NCCL, NVSHMEM)
  • Experience building and shipping products to enterprise customers.
  • GPU programming experience (CUDA, OAI TRITON or CUTLASS).

What you'll be doing:

  • Performance optimization, analysis, and tuning of DL models in various domains like LLM, Multimodal and Generative AI.
  • Scale performance of DL models across different architectures and types of NVIDIA accelerators.
  • Contribute features and code to NVIDIA’s inference libraries, vLLM and SGLang, FlashInfer and LLM software solutions.
  • Work with cross-collaborative teams across frameworks, NVIDIA libraries and inference optimization innovative solutions.

Perks and benefits:

  • NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization.
  • Highly competitive salaries.
  • Extensive benefits package.
  • Work environment that promotes diversity, inclusion, and flexibility.
  • Equal opportunity employer committed to fostering a supportive and empowering workplace for all.
AI Summary ✨
NVIDIA logo

NVIDIA

Italy, Poland

Experience: Senior
Posted: May 28, 2025
Last seen: 2 hours ago
Python
machinelearning

Why we track NVIDIA

NVIDIA has become one of the most important companies in tech thanks to AI and GPU computing. They have EU roles across several countries. If you're interested in hardware, CUDA, or ML infrastructure, they're hard to beat.

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