Senior Deep Learning Engineer

is challenge?

What you'll be doing:

• Implement deep learning models from multiple data domains (CV, NLP/LLMs, ASR, TTS, RecSys and others) in multiple DL frameworks (PyT, JAX, TF2, DGL and others)

• Implement and test new SW features (Graph Compilation, reduced precision training) that use the most recent HW functionalities.

• Analyze, profile, and optimize deep learning workloads on state-of-the-art hardware and software platforms.

• 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

What we need to see:

• 3+ years of experience in DL model implementation and SW Development

• BSc, MS or PhD degree in Computer Science, Computer Architecture or related technical field

• Excellent Python programming skills, extensive knowledge of at least one DL Framework (PyTorch, TensorFlow, JAX, MxNet)

• Strong problem solving and analytical skills

• Algorithms and DL fundamentals

Ways to stand out from the crowd:

• Experience in performance measurements and profiling

• Experience with containerization technologies such as Docker

• GPU programming experience (CUDA or OpenCL) is a plus but not required.

• Solid understanding of Linux environments

• Knowledge and love for DevOps/MLOps practices for Deep Learning-based product's development.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most brilliant and forward-thinking people in the world working for us. If you're creative and autonomous, we want to hear from you! We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.