Deep Learning Engineer - LLM and VLM Model Compression

Requirements:

• 8+ years of experience in Deep Learning and SW Development.
• BSc, MS or PhD degree in Computer Science, Computer Architecture or related technical field.
• Hands-on experience with LLM or VLM model training or inference.
• Excellent Python programming skills.
• Extensive knowledge of at least one DL Framework (PyTorch, TensorFlow, JAX, MxNet) with practical experience in PyTorch required.
• Strong problem solving and analytical skills.
• Algorithms and DL fundamentals.

Nice to haves:

• Experience applying and implementing model compression techniques such as pruning, NAS, distillation, and quantization.
• Experience building deep learning frameworks for training, inference, model compression, or related topic.
• GPU programming experience (CUDA or OpenCL) is a plus but not required.
• First-author publication in a top-tier deep learning or AI conference.

What you'll be doing:

• Design and implement a deep learning framework for compressing large language and vision-language models to deliver highly optimized, high-performance AI systems used worldwide.
• Develop and integrate new algorithms for pruning, NAS, and distillation in collaboration with NVIDIA researchers and engineers.
• Experiment with compressing the latest LLMs and VLMs, analyzing their performance and behavior across diverse workloads.
• Collaborate with researchers and engineers across NVIDIA, providing guidance on improving the design, usability and performance of workloads.
• Lead best-practices for building, testing, and releasing DL software.

Perks and Benefits:

• NVIDIA is widely considered one of the technology world’s most desirable employers.
• Equal opportunity employer that values diversity.
• Competitive base salary based on location, experience, and pay of employees in similar positions.