AI-Native Numerical Methods Scientist

2100 NVIDIA USA; California (MO); On-site; USD 224,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking an applied researcher to connect machine learning with numerical algorithms, invent AI-native numerical methods, and improve solvers on modern GPUs. You will work across NVIDIA solver, simulation, and computational engineering platforms with researchers and industry partners.

The role requires a PhD or equivalent, 5+ years of experience, and a strong background in ML and scientific computing. Proficiency in PyTorch/JAX, Python, and GPU computing is essential for success.

Qualifications

• PhD or equivalent experience in computer science, ML, scientific computing, applied mathematics, computational engineering, physics, or related field.
• 5 years of relevant work/research experience.
• Background in ML and scientific computing with evidence of connecting ML to numerical algorithms.
• Experience with PyTorch, JAX, or comparable DL frameworks, plus Python and GPU computing.
• Working knowledge of PDEs, sparse linear algebra, iterative solvers, preconditioning, finite element/finite volume methods, optimization, or differentiable programming.
• Research record in scientific ML, numerical linear algebra, or differentiable simulation integrated with numerical solvers.
• Strong communication skills for collaboration across AI research, numerical methods, product, and production teams.

Responsibilities

• Research AI-assisted numerical methods to improve convergence, stability, accuracy, robustness, and wall-clock performance for large-scale simulations.
• Invent learned coarse spaces, learned preconditioners, AI-guided multigrid, solver-control policies, differentiable solver components, and hybrid numerical/ML algorithms.
• Build solver-in-the-loop pipelines using residual histories, discretized operators, meshes, geometry, and performance counters.
• Define evaluation methods to measure numerical impact like convergence rate, failure rate, conservation, memory footprint, and speedup.
• Collaborate with NVIDIA Research, CUDA-X, Warp, PhysicsNeMo, and related teams; help define NVIDIA's applied research agenda.

Skills

Machine learning

Scientific computing

Research experience

Communication skills

Education

PhD or equivalent

Tools

PyTorch

JAX

Python

GPU computing

Job description

NVIDIA is seeking an applied researcher to connect machine learning with numerical algorithms, invent AI-native numerical methods, and improve solvers on modern GPUs. You will work across NVIDIA solver, simulation, and computational engineering platforms with researchers and industry partners.

The role requires a PhD or equivalent, 5+ years of experience, and a strong background in ML and scientific computing. Proficiency in PyTorch/JAX, Python, and GPU computing is essential for success.