Differentiable Simulation Research Intern - Summer 2027 - CA, Santa Clara, United States
$38 - $94 USD yearly
Originally posted 12 October 2026 by the employer.
About the role
This internship focuses on research into scalable differentiable algorithms, including adjoint and automatic differentiation methods. The work will connect simulations with experimental data for calibration and data assimilation using AI/ML methods.
What you'll do
- Prototype GPU-native solvers with adjoint and automatic differentiation techniques for engineering simulations.
- Integrate AI-based methods with simulation algorithms for parameter calibration, inverse problems, and data assimilation using experimental or simulation data.
- Co-design numerical algorithms and differentiation strategies for GPU parallelism, memory hierarchy, mixed precision, reduced synchronization, and distributed multi-GPU execution.
- Evaluate numerical accuracy, convergence, gradient quality, performance, and scalability on workloads in CFD, mechanics, thermal systems, and multiphysics.
- Identify promising methods and help move them toward reusable capabilities in CUDA-X libraries.
What you'll need
- Pursuing a PhD in applied mathematics, scientific computing, computational engineering, computer science, mechanical engineering, aerospace engineering, or equivalent program area.
- Strong foundations in algorithms related to PDEs, numerical linear algebra, iterative solvers, optimization, or scientific computing.
- Research experience with adjoint methods, automatic differentiation, inverse problems, data assimilation, gradient-aware simulation approaches, or a related area.
- Experience writing numerical software in Python and C++, with familiarity with parallel or GPU computing.
- Ability to design computational experiments, evaluate numerical and performance tradeoffs, and communicate technical results clearly.
Skills: differentiable algorithms, GPU-native solvers, AI-based methods, CUDA-X libraries, scientific computing
This role has been open 2 days — well below the 50-day median for Infrastructure/Platform Software roles.
Infrastructure/Platform Software · Infrastructure Platform
|
Open roles in category
973
|
Median days open
50 d
|
Median salary
$235k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | NVIDIA | All employers we track in this specialty (973 roles · 85 employers) |
|---|---|---|
| Open roles in this specialty | 281 | 973 |
| Open roles in the wider Software, Firmware & Systems family | 993 | 6141 · 145 employers |
| Median days open | 45 d | 50 d (−5 d vs this employer) |
| Median salary (USD postings) | — | $235k |
Skills observed across this category: differentiable algorithms, GPU-native solvers, AI-based methods, CUDA-X libraries, scientific computing
Who's hiring in this category
- NVIDIA (this employer) · 289 open roles · median 44 d
- Qualcomm · 61 open roles · median 57 d
- AMD · 57 open roles · median 21 d
- Graphcore · 44 open roles · median 90 d
- Intel Corporation · 40 open roles · median 9 d
- Cerebras · 39 open roles · median 80 d
How we counted: 973 open Infrastructure/Platform Software (Infrastructure Platform) roles from 85 employers tracked in the SemiconductorJobs index, counted 15 Oct 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Software, Firmware & Systems family row. Figures refresh nightly.