We are now seeking a Senior Deep Learning Software Engineer for Recipe Pathfinding. NVIDIA is looking for experienced software engineers to help rethink and create SW systems to accelerate the discovery of new low-precision and sparsity recipes. A recipe defines which operators in an LLM are transformed into low-precision and/or sparsified variants, thereby unlocking efficiency gains.
Recipes can be statically defined at model load time or dynamically adapting to a layer’s input distribution. Recipes can incorporate and compose algorithmic techniques like rotations or low-rank decompositions to tame aggressors like outliers. We are a team committed to developing next-generation SW to make use of novel HW features on Blackwell, Rubin, and beyond. The scope spans all phases of the LLM life cycle: pre training, post training, and generation. This is a coding-heavy role focused on infrastructure, tooling, and performance. Making these recipes fast is critical to minimize spend – each production run can easily cost millions of dollars. The candidate's work will directly support NVIDIA's internal SW systems for supporting recipe prototyping. Your work is a component of our SW productization story in libraries like Megatron-LM and Transformer Engine.
What you'll be doing:
Create well-designed and well-tested SW systems and PoCs to support recipe exploration for research settings
Analyze and prototype state-of-the-art methods for quantization and sparsity
Benchmark, profile, and optimize LLM workloads in cluster settings
Keep developer and researcher productivity and efficiency high by removing obstacles (e.g., slow CI systems, slow training systems)
Participate in code reviews, address code review feedback if applicable.
What we need to see:
PhD, M.S. degree or equivalent experience in Computer Science or a related field.
5+ years of experience in a relevant software engineering role.
Strong software engineering background with a focus on building concise and well-tested code.
Proficient in Python.
Firsthand experience working with ML accelerators.
Experience with PyTorch or similar framework.
Experience with performance optimization and debugging
Strong written and oral communication skills
Ways to stand out from the crowd:
Proficient in precision and numerics for ML
Experience with CUDA and coding with C++
Strong foundation in LLM pre training, post training, or generation
The GPU started out as the engine for simulating human imagination, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA’s GPU runs deep learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Today, NVIDIA GPUs are used broadly for deep learning, and NVIDIA is increasingly known as “the AI computing company.”
Widely considered to be one of the technology world’s most desirable employers, NVIDIA has some of the most forward-thinking and hardworking people in the world inventing the future for us. Are you creative and collaborative software engineer seeking new challenges? If so, we want to hear from you! Come, join us and help build the real-time, cost-effective AI computing platform driving our success in this exciting and quickly growing field.
The base salary range is 184,000 USD - 356,500 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.
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NVIDIA is a publicly traded, multinational technology company headquartered in Santa Clara, California. NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, and ignited the era of modern AI.
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