As a Senior HPC Performance Engineer at NVIDIA, you will join a team dedicated to advancing scientific machine learning frameworks, focusing on digital biology and high-performance computing. Your daily responsibilities include designing and implementing computationally efficient features for large-scale ML training frameworks using CUDA and other low-level acceleration techniques, optimizing the performance of critical business models through hardware and software improvements, developing HPC software stacks for atomistic modeling in digital biology, and collaborating with various research teams to drive testing and maintenance of algorithms. Ideal candidates hold advanced degrees in quantitative fields like Computer Science or Computational Biophysics and have extensive experience in parallel programming with C++, Python, CUDA, and modern ML frameworks such as PyTorch and JAX. Additionally, familiarity with HPC solutions for biology and chemistry is essential, along with a proven track record of technical leadership and strong communication skills.
Skills
CUDA
Python
C++
PyTorch
JAX
Warp
HPC
Distributed Learning
Atomistic Modeling
CI/CD
Git
Linux
NVIDIA DGX Systems
GPU Programming
Parallel Computing
Data Structures
Algorithm Design
Machine Learning Frameworks
Scientific AI Codebases
Computational Chemistry
Digital Biology
What you'll do
Design and implement computationally efficient features for large-scale ML training frameworks using CUDA.
Optimize performance of business-critical ML models through hardware and software acceleration techniques.
Develop and maintain HPC software stack for atomistic modeling and generative machine learning in digital biology.
Drive testing and maintenance of algorithms and software modules to ensure reliability and efficiency.
Collaborate on pioneering AI for Science codebase, contributing new kernels and acceleration features.
What we're looking for
Advanced degree in quantitative field or equivalent experience in performance engineering.
Expertise in C++, Python, CUDA, and modern ML frameworks like PyTorch, JAX.
Proven track record in designing and implementing high-performance software products.
Experience with HPC solutions for biology/chemistry research problems.
Strong technical leadership skills and ability to collaborate across teams.
Familiarity with pioneering languages and geometric models in AI for science.
Capable of self-direction, learning from others, and contributing to scientific codebases.
Market check
Salary context
This
$184,000–$287,500
range sits above
70%
of similar postings on FindRole.
Peer median band
$170,850–$262,400
Median floor and ceiling across peers.
Typical midpoint (25–75%)
$181,758–$246,150
Middle half of comparable postings.
Based on 240 comparable postings.*
* 240 is the maximum number of comparable postings sampled.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
802 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 798 roles with salary data.
Remote (Us, Ma, Westford, US)139 days ago
$224,000–$356,500
Linux
Slurm
CUDA-Q
cuQuantum
NVQlink
Python
C++
NVIDIA
HPC
GPU
Neutral atom
Trapped ion
Superconducting
Photonic
Qiskit
Cirq
PennyLane
Braket
Networking
Storage
Data center infrastructure
Quantum computing