Used Tools & Technologies
Not specified
Required Skills & Competences ?
Python @ 7 Machine Learning @ 4 TensorFlow @ 7 LLM @ 4 PyTorch @ 7 GPU @ 7Details
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. They are now focusing on AI to define the next era of computing, where GPUs operate as the brains of computers, robots, and self-driving cars that understand the world.
Responsibilities
- Innovate and develop new machine learning compiler and systems technologies.
- Design, implement, and optimize compilers for high-impact AI workloads.
- Build efficient just-in-time domain-specific compiler and runtime for generative AI workloads.
- Co-design learning system solutions with current and future ML compiler and algorithm technologies.
- Collaborate closely with internal NVIDIA software and hardware teams to build high-impact machine learning acceleration solutions.
Requirements
- Bachelor’s degree in Computer Science, Electrical Engineering, or related field (MS or PhD preferred).
- 4+ years of academic or industry experience with ML/DL systems development, preferably for compilers.
- Strong experience with deep learning frameworks such as PyTorch, JAX, TensorFlow, ONNX.
- Strong programming skills in Python and C/C++.
- Expertise in AI frameworks like PyTorch, TensorFlow, and ONNX.
Ways to Stand Out
- Expertise in machine compilers such as Apache TVM, MLIR.
- Expertise in domain-specific compiler and library solutions for LLM inference and training (e.g., FlashInfer, Flash Attention).
- Strong experience in GPU performance optimizations.
- Strong experience in machine learning systems research and productization.
- Open source project ownership or contributions.
Benefits
- Competitive salaries ranging from 148,000 USD to 287,500 USD depending on location, experience, and peers.
- Eligibility for equity and benefits.
- Commitment to a diverse work environment and equal opportunity employment.