Senior Machine Learning Performance Engineer - Physics

About This Role

As a Senior Machine Learning Performance Engineer specializing in Physics, you will contribute to building and optimizing the NVIDIA PhysicsNeMo AI framework. This framework addresses cutting-edge scientific and engineering problems such as climate challenges, digital twins, and drug development, working with academic and industrial partners.

Responsibilities

• Develop a leading machine learning framework, NVIDIA PhysicsNeMo, for academic and industrial partners to construct digital twins and machine learning simulation surrogates for real-world science and engineering problems.
• Collaborate with internal project teams to validate applications built using the framework on NVIDIA's products.
• Characterize and optimize scientific AI workloads on the latest NVIDIA platforms.
• Stay up to date with the latest research and innovations in deep learning techniques, implementing and experimenting with new ideas to enhance NVIDIA's deep learning technologies with a focus on simulations.

Requirements

• BS or MS degree (PhD preferred) in computer science, mathematics, computational science/engineering, or related technical field or equivalent experience
• 5+ years of relevant experience
• Strong Python programming skills
• Familiarity with containers, numeric libraries, modular software design, distributed computing, and/or high-performance storage systems.
• Good knowledge of state-of-the-art DNN architectures and machine learning techniques and algorithms (graph networks, diffusion models, reinforcement learning etc.) with experience in developing or using major deep learning frameworks (PyTorch, Tensorflow, JAX etc.)
• Experience with solving and using machine learning for real-world problems involving scientific/engineering simulations (e.g., industrial, life sciences, high energy physics, earth sciences)
• Strong analytical skills
• Solid written and oral communications skills
• Good teamwork and interpersonal skills

Qualifications

• BS or MS degree (PhD preferred) in computer science, mathematics, computational science/engineering, or related technical field or equivalent experience
• 5+ years of relevant experience.

Nice to Have

• Experience with scientific visualization
• Experience with performance measurement tools, such as NVIDIA Nsight Systems
• Experience with multi-node systems with data-parallel and model parallel programming
• Experience with CUDA, or python kernel languages such as Triton or NVIDIA Warp
• Usage of nonlinear simulation tools and techniques, usage of major simulation codes (opensource and/or commercial)
• Experience with High Performance Computing for Scientific AI, or end-to-end training and inference optimization
• Published papers in the field of AI in scientific computing

Skills

* Required skills

Benefits