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Benefits & Perks
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Machine Learning
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NSight Systems
NSight Compute
NCCL
We are seeking a Senior AI/ML Performance and Efficiency Engineer, GPU Clusters at NVIDIA to join our AI Efficiency efforts. As an Engineer, you will have a pivotal role in enhancing efficiency for our researchers by implementing progressions throughout the entire stack. Your main task will revolve around collaborating closely with customers to pinpoint and address infrastructure and application deficiencies, facilitating groundbreaking AI and ML research on GPU Clusters. Together, we can craft potent, effective, and scalable solutions as we mold the future of AI/ML technology!
What you will be doing:
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Collaborate closely with our AI/ML researchers to make their ML models more efficient leading to significant productivity improvements and cost savings
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Build tools, frameworks, and apply ML techniques to detect & analyze efficiency bottlenecks and deliver productivity improvements for our researchers
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Work with researchers working on a variety of innovative ML workloads across Robotics, Autonomous vehicles, LLM’s, Videos and more
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Collaborate across the engineering organizations to deliver efficiency in our usage of hardware, software, and infrastructure
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Proactively monitor fleet wide utilization patterns, analyze existing inefficiency patterns, or discover new patterns, and deliver scalable solutions to solve them
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Keep up to date with the most recent developments in AI/ML technologies, frameworks, and successful strategies, and advocate for their integration within the organization.
What we need to see:
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BS or similar background in Computer Science or related area (or equivalent experience)
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Minimum 5+ years of experience designing and operating large scale compute infrastructure
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Strong understanding of modern ML techniques and tools
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Experience investigating, and resolving, training & inference performance end to end
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Debugging and optimization experience with NSight Systems and NSight Compute
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Experience with debugging large-scale distributed training using NCCL
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Proficiency in programming & scripting languages such as Python, Go, Bash, as well as familiarity with cloud computing platforms (e.g., AWS, GCP, Azure) in addition to experience with parallel computing frameworks and paradigms.
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Dedication to ongoing learning and staying updated on new technologies and innovative methods in the AI/ML infrastructure sector.
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Excellent communication and collaboration skills, with the ability to work effectively with teams and individuals of different backgrounds
Ways to stand out from the crowd:
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Background with NVIDIA GPUs, CUDA Programming, NCCL and MLPerf benchmarking
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Experience with Machine Learning and Deep Learning concepts, algorithms and models
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Familiarity with Infini Band with IBOP and RDMA
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Understanding of fast, distributed storage systems like Lustre and GPFS for AI/HPC workloads
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Familiarity with deep learning frameworks like Py Torch and Tensor Flow
NVIDIA offers competitive salaries and a comprehensive benefits package. Our engineering teams are growing rapidly due to outstanding expansion. If you're a passionate and independent engineer with a love for technology, 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 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until February 24, 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.
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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
4.1
10 reviews
Work Life Balance
3.5
Compensation
4.2
Culture
4.3
Career
4.5
Management
4.0
75%
Recommend to a Friend
Pros
Great culture and supportive environment
Smart colleagues and excellent people
Cutting-edge technology and learning opportunities
Cons
Team-dependent experience and outcomes
Work-life balance issues with long hours
Politics and influence over competence
Salary Ranges
47 data points
Junior/L3
Mid/L4
Junior/L3 · Analyst
7 reports
$170,275
total / year
Base
$130,981
Stock
-
Bonus
-
$155,480
$234,166
Interview Experience
7 interviews
Difficulty
3.1
/ 5
Experience
Positive 0%
Neutral 86%
Negative 14%
Interview Process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Interview
5
System Design Interview
6
Team Review
Common Questions
Coding/Algorithm
System Design
Technical Knowledge
Behavioral/STAR
News & Buzz
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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·
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.
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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.
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·
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.
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NaNw ago