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Senior Deep Learning Software Engineer, Inference and Model Optimization
2 Locations
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On-site
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Full-time
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1w ago
NVIDIA is at the forefront of the generative AI revolution! The Algorithmic Model Optimization Team specifically focuses on optimizing generative AI models such as large language models (LLM) and diffusion models for maximal inference efficiency using techniques ranging from neural architecture search and pruning to sparsity, quantization, and automated deployment strategies. Our work includes conducting applied research to improve model efficiency as well as developing an innovative software platform (TRT Model Optimizer). Our software is used both internally across NVIDIA and externally by research and engineering teams alike developing best-in-class AI models.
We are now looking for a Senior Deep Learning Software Engineer to develop and scale up our automated inference and deployment solution. As part of the team, you will be instrumental in pushing the limits of inference efficiency and large-scale, automated deployment. Your work will touch upon fundamental aspects of a typical machine learning stack including working in high-level frameworks like Py Torch and Hugging Face to developing and improving high-performance kernel implementations in CUDA, TRT-LLM, and Triton. This is an exceptional opportunity for passionate software engineers straddling the boundaries of research and engineering, with a strong background in both machine learning fundamentals and software architecture & engineering.
What you’ll be doing:
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Train, develop, and deploy state-of-the generative AI models like LLMs and diffusion models using NVIDIA's AI software stack.
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Leverage and build upon the torch 2.0 ecosystem (Torch Dynamo, torch.export, torch.compile, etc...) to analyze and extract standardized model graph representation from arbitrary torch models for our automated deployment solution.
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Develop high-performance optimization techniques for inference, such as automated model sharding techniques (e.g. tensor parallelism, sequence parallelism), efficient attention kernels with kv-caching, and more.
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Collaborate with teams across NVIDIA to use performant kernel implementations within our automated deployment solution.
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Analyze and profile GPU kernel-level performance to identify hardware and software optimization opportunities.
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Continuously innovate on the inference performance to ensure NVIDIA's inference software solutions (TRT, TRT-LLM, TRT Model Optimizer) can maintain and increase its leadership in the market.
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Play a pivotal role in architecting and designing a modular and scalable software platform to provide an excellent user experience with broad model support and optimization techniques to increase adoption.
What we need to see:
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Masters, PhD, or equivalent experience in Computer Science, AI, Applied Math, or related field.
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3+ years of relevant work or research experience in Deep Learning.
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Excellent software design skills, including debugging, performance analysis, and test design.
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Strong proficiency in Python, Py Torch, and related ML tools (e.g. Hugging Face).
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Strong algorithms and programming fundamentals.
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Good written and verbal communication skills and the ability to work independently and collaboratively in a fast-paced environment.
Ways to stand out from the crowd:
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Contributions to Py Torch, JAX, or other Machine Learning Frameworks.
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Knowledge of GPU architecture and compilation stack, and capability of understanding and debugging end-to-end performance.
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Familiarity with NVIDIA's deep learning SDKs such as TensorRT.
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Prior experience in writing high-performance GPU kernels for machine learning workloads in frameworks such as CUDA, CUTLASS, or Triton.
Increasingly known as “the AI computing company” and widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. Are you creative, motivated, and love a challenge? If so, we want to hear from you! Come, join our model optimization group, where you can help build real-time, cost-effective computing platforms driving our success in this exciting and rapidly-growing field.
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 March 1, 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
L3
L4
L5
L3 · Data Scientist IC2
0 reports
$177,542
total / year
Base
-
Stock
-
Bonus
-
$150,910
$204,174
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
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
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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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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