
Pioneering accelerated computing and AI
Senior Application Engineer
Required skills
Machine Learning
NVIDIA is seeking Senior Application Engineer for technical collaboration on Materials and Chemical Discovery using AI. Sr Application Engineers are drawn from elite developers and scientists who enjoy working with the latest in GPU hardware and AI Models. An ideal candidate is someone who is entrepreneurial, self-motivated, creative and passionate about bringing the latest techniques to customers who want to accelerate the discovery of novel materials using Predictive AI or Generative AI. Discovery of new materials and chemicals is one of the core workloads across a broad range of customers including supercomputing, higher education, manufacturing, semiconductors, agriculture, etc.
As a Sr. Application Engineer, you will be part of the team comprising Product Managers and Strategic Alliance Partners and working with customers.
What you will be doing:
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Work directly with developers and researchers who are building, fine-tuning or optimizing AI models for Chemistry and Material discovery.
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Collaborate with publishers of open-source applications, datasets, frameworks used for AI Driven Chemical and Materials discovery and display their ability to use NVIDIA ALCHEMI.
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Profile, benchmark and suggest optimization strategies to developers building AI models and Agentic AI workflows for discovering novel materials and formulations.
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Present at workshops as the domain expert.
What we need to see:
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Degree in Chemistry, Material Science or related field (Ph.D. or Masters preferred) or equivalent experience.
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4+ years of experience with developing or using AI models for chemistry and material discovery using popular deep learning frameworks on CPUs and GPUs.
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Proven ability to benchmark and compare domain specific AI Models for Materials discovery.
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Strong written and oral communication skills with the ability to effectively articulate the value proposition to technical and non-technical audiences
Ways to stand out from the crowd:
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Experience with using AI frameworks e.g Py Troch, JAX
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Background in the development of chemistry/materials simulation software packages, machine learning interatomic potentials (MLIP) design, or generative AI for chemistry/material science.
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Knowledge about NV GPU and CUDA- X libraries.
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About NVIDIA

NVIDIA
PublicA computing platform company operating at the intersection of graphics, HPC, and AI.
10,001+
Employees
Santa Clara
Headquarters
$4.57T
Valuation
Reviews
10 reviews
4.4
10 reviews
Work-life balance
2.8
Compensation
4.5
Culture
4.2
Career
4.3
Management
3.8
78%
Recommend to a friend
Pros
Cutting-edge technology and innovation
Excellent compensation and benefits
Great team culture and collaboration
Cons
High pressure and expectations
Poor work-life balance and long hours
Fast-paced environment leading to burnout
Salary Ranges
79 data points
L3
L4
L5
L3 · Data Scientist IC2
0 reports
$177,542
total per year
Base
-
Stock
-
Bonus
-
$150,910
$204,174
Interview experience
5 interviews
Difficulty
3.0
/ 5
Interview process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
Common questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Past Experience
Latest updates
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.
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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.
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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.
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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.
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