招聘

Senior ML Framework Performance Engineer - AI for Science at Scale
US, CA, Santa Clara
·
On-site
·
Full-time
·
1mo ago
薪酬
$184,000 - $287,500
福利待遇
•Equity
必备技能
Performance engineering
Machine Learning
PyTorch
JAX
Model parallelism
Distributed learning
Python
Scientific computing
NVIDIA has become the platform upon which every new AI-powered application is built. We are seeking a Senior Machine Learning Performance Engineer to join our team of scientists and engineers passionate about building the next generation of scientific machine learning (ML) frameworks. Starting with digital biology, we will enable powerful and efficient ML methods through collaborations with industry and academic partners. Together, we will advance NVIDIA’s capacity to accelerate AI for Science and industries that depend on it.
What you'll be doing:
-
Design performance and accuracy evaluation frameworks and carry out evaluations of pioneering ML models used in scientific discovery, in particular the ones relating to atomistic modeling. Identify end-to-end model execution bottlenecks, design and implement solutions at scale such as model parallelism.
-
Drive the testing and maintenance of the algorithms and software stack used in the AI for Science applications within the company and in the open source community
-
Stay up-to-date on the latest machine learning technologies and evaluate their potential as solutions to accuracy and/or computational performance bottlenecks.
-
Collaborate with multiple high performance computing, AI infrastructure, and research teams
-
Contribute to documentation or educational content relating to product
What we need to see:
-
Advanced degree in a quantitative field such as Computer Science, Computational Biophysics, Computational Chemistry, Physics, Mathematics, or equivalent experience
-
5+ years of relevant experience
-
Consistent track record of performance engineering in large scale AI model training and inference applications, and deep understanding of compute bottlenecks of these models, and of paradigms of parallelism in these applications such as model parallelism.
-
Expertise in modern machine learning frameworks such as Py Torch, JAX, Warp and distributed learning strategies within them
-
Up-to-date knowledge of ML research in scientific discovery and in atomistic modeling
-
Experience with software design, building, packaging and launching software products based on ML research or atomistic simulation tools
-
Recognized for technical leadership contributions, capable of self-direction, and ability to learn from and teach others
-
You should display strong communication skills, be organized and self-motivated, and play well with others (be an excellent teammate!)
Ways to stand out from the crowd:
-
Contributor to major scientific codebase for atomistic modeling or AI for science
-
Experience with CUDA/Triton programming or familiarity with CUDA/Triton extensions of ML frameworks
With highly competitive salaries and a comprehensive benefits package, Nvidia is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking, resourceful and dedicated people in the world working with us and our engineering teams are growing fast in some of the hottest innovative fields: Quantum Computing, Artificial Intelligence, and Autonomous Vehicles. Are you a creative and autonomous engineer with a real passion for machine learning, computational biology and chemistry, data science & parallel computing? If so, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until February 21, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
总浏览量
0
申请点击数
0
模拟申请者数
0
收藏
0
相似职位

Senior CPU Engineer
Qualcomm · Santa Clara, California, United States of America

Staff Design for Test STA Engineer
Tenstorrent · Santa Clara, California, United States

Staff Optical Engineer
Marvell · Santa Clara, CA

Senior Staff Verification Engineer
Marvell · Santa Clara, CA

Sr Technical Marketing Engineer (AIOPs and NextGen Firewalls) Santa Clara, CA 01/26/2026
Palo Alto Networks · santa clara
关于NVIDIA

NVIDIA
PublicA computing platform company operating at the intersection of graphics, HPC, and AI.
10,001+
员工数
Santa Clara
总部位置
$4.57T
企业估值
评价
4.1
10条评价
工作生活平衡
3.5
薪酬
4.2
企业文化
4.3
职业发展
4.5
管理层
4.0
75%
推荐给朋友
优点
Great culture and supportive environment
Smart colleagues and excellent people
Cutting-edge technology and learning opportunities
缺点
Team-dependent experience and outcomes
Work-life balance issues with long hours
Politics and influence over competence
薪资范围
73个数据点
L3
L4
L5
L3 · Data Scientist IC2
0份报告
$177,542
年薪总额
基本工资
-
股票
-
奖金
-
$150,910
$204,174
面试经验
7次面试
难度
3.1
/ 5
体验
正面 0%
中性 86%
负面 14%
面试流程
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Interview
5
System Design Interview
6
Team Review
常见问题
Coding/Algorithm
System Design
Technical Knowledge
Behavioral/STAR
新闻动态
Negotiating NVIDIA's Offer
Base, stock, and sign-on negotiable. Recruiters invested in closing candidates. CEO reviews all 42K employee salaries monthly. Stock growth has made many employees millionaires.
News
·
NaNw ago
NVIDIA Company Reviews
WLB rated 3.9/5 (lowest category). 64% satisfied with WLB but 53% feel burnt out. Compensation rated 4.4-4.5/5. Experience highly team-dependent.
News
·
NaNw ago
NVIDIA Interview Discussions
Technical bar is high with 4-6 rounds. Process takes 4-8 weeks. Expect C++ questions, LeetCode medium, and system design. Difficulty rated 3.16/5.
News
·
NaNw ago
NVIDIA Culture Discussions
Team-dependent experience; sink-or-swim culture that rewards high performers but can be overwhelming. No politics, flat structure, but demanding workload with some teams requiring evening/weekend work.
News
·
NaNw ago