Top 30 Quantization Transformer Architecture accelerator Jobs

Senior Deep Learning Software Engineer, TensorRT Performance
NVIDIA —Santa Clara, CA
- $152,000 - $287,500 a year
- Full-time
- Computer science
- Computer Science
- 3 years
Embedded AI Tooling Engineer
Analog Devices —Wilmington, MA
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Edge ML Software Engineer (Model Optimization-PICO) - San Jose
ByteDance —San Jose, CA
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AI Accuracy Architect
Qualcomm —San Diego, CA
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AI Inference Engineer
quadric, Inc —Burlingame, CA
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- 5 years
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Lead Compiler Engineer
Neurophos —Austin, TX
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- 5 years
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Principal Engineer/Manager
Qualcomm —San Diego, CA
- $206,900 - $310,300 a year
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Performance Architect
Sandisk —Milpitas, CA
- Full-time
- Hybrid work
- System design
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- 3 years
- Health savings account
- AD&D insurance
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AI Engineer, ML Inference Optimization, Tesla AI
Tesla —Palo Alto, CA
- $176,000 - $420,000 a year
- Full-time
- System design
- C++
- In-person
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Software Engineer, Model Hardware CoDesign
Tesla —Palo Alto, CA
- $140,000 - $390,000 a year
- Full-time
- Research
- In-person
- Senior level
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- Health savings account
LLM Inference Frameworks and Optimization Engineer
Together AI —San Francisco, CA
- $160,000 - $230,000 a year
- Full-time
- Mid-level
- 3 years
- Analysis skills
- Health insurance
Kernel Optimization Software Engineer, AI Hardware
Tesla —Palo Alto, CA
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- Full-time
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- Engineering
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AI/ML ASIC Architect
Sandisk —Milpitas, CA
- Full-time
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- Health savings account
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Senior Autonomy Engineer
Brain Corp —San Diego, CA
- $151,545 - $183,449 a year
- Computer Science
- 5 years
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AI Compute Architect, AI Hardware
Tesla —Palo Alto, CA
- $128,000 - $312,000 a year
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- Computer science
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AI Compiler and Performance Engineer
ElastixAI INC. —Seattle, WA
- Full-time
- Hybrid work
- Computer Science
- Bachelor of Science
- System design
- Commuter assistance
- Paid parental leave
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Staff Autonomy Engineer
Brain Corp —San Diego, CA
- $169,525 - $205,215 a year
- On call
- 7 years
- Computer Science
- Office
- Health savings account
- Paid holidays
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Staff CV Applied Research Engineer, Edge AI
SimpliSafe —Boston, MA
- $183,300 - $268,800 a year
- Hybrid work
- System design
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Autonomous Driving Multimodal Model Algorithm Engineer
Black Sesame Technologies Inc —San Jose, CA
- $130,000 - $400,000 a year
- Full-time
- Computer Science
- C++
- Doctor of Philosophy
- Health savings account
- Health insurance
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13d
AI Accelerator Silicon Architect
MatX —Mountain View, CA
- $120,000 - $600,000 a year
- Full-time
- Hybrid work
- Office
- Analysis skills
- US work authorization
- Paid parental leave
- Health savings account

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Senior Deep Learning Software Engineer, TensorRT Performance

NVIDIA -
Santa Clara, CA

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Job Details

Full-time
$152,000 - $287,500 a year

Qualifications

Performance tuning
Software engineering
Software coding
System performance optimization
AI platforms (beyond public GPTs)
Computational framework
Machine learning libraries
Machine learning frameworks

Full Job Description

We are now looking for a Senior Deep Learning Software Engineer, TensorRT Performance! NVIDIA is seeking an experienced Deep Learning Engineer passionate about analyzing and improving the performance of NVIDIA’s inference ecosystem! NVIDIA is rapidly growing our research and development for Deep Learning Inference and is seeking excellent Software Engineers at all levels of expertise to join our team. Companies around the world are using NVIDIA GPUs to power a revolution in deep learning, enabling breakthroughs in areas like Generative AI, Recommenders and Vision that have put DL into every software solution. Join the team that builds the software to enable the performance optimization, deployment and serving of these DL inference solutions. We specialize in developing GPU-accelerated deep learning inference software like TensorRT, DL benchmarking software and performant solutions to deploy and serve these models.

Collaborate with the deep learning community to integrate TensorRT into OSS frameworks like TensorRT-EdgeLLM and PyTorch. Identify performance opportunities and optimize SoTA models across the spectrum of NVIDIA accelerators, from datacenter GPUs to edge SoCs. Implement graph compiler algorithms, frontend operators and code generators across NVIDIA’s inference ecosystem. Work and collaborate with a diverse set of teams involving workflow improvements, performance modeling, performance analysis, kernel development and inference software development.

What you'll be doing:

Establish groundbreaking performance benchmarking methodologies and analysis workflows and identify performance issues and opportunities for NVIDIA’s inference ecosystem (e.g. TensorRT/TensorRT-EdgeLLM/Torch-TensorRT)
Contribute features and code to NVIDIA/OSS inference frameworks including but not limited to TensorRT/TensorRT-EdgeLLM/Torch-TensorRT.
Develop new model pipelines for NVIDIA’s inference ecosystem with optimized performance including but not limited to areas like quantization, scheduling, memory management, and distributed inference to set the gold standard for Gen AI performance.
Work with cross-collaborative teams inside and outside of NVIDIA across generative AI, automotive, robotics, image understanding, and speech understanding to set directions and develop innovative inference solutions.
Scale performance of deep learning models across different architectures and types of NVIDIA accelerators.

What we need to see:

Bachelors, Masters, PhD, or equivalent experience in relevant fields (Computer Science, Computer Engineering, EECS, AI).
At least 3 years of relevant software development experience.
Strong C++, Python programming and software engineering skills
Experience with DL frameworks (e.g. PyTorch, JAX, TensorFlow, ONNX) and inference libraries (e.g. TensorRT, TensorRT-LLM, vLLM, SGLang, FlashInfer).
Experience with performance analysis and performance optimization

Ways to stand out from the crowd:

Strong foundation and architectural knowledge of GPUs.
Deep understanding of modern deep learning models and workloads (e.g. Transformers, Recommenders, ASR, TTS, Visual Understanding).
Proficiency in one of the deep learning programming domain specific languages (e.g. CUDA/TileIR/CuTeDSL/cutlass/Triton).
Prior contributions to major LLM inference frameworks (e.g. vLLM) or prior experience with graph compilers in deep learning inference (e.g. TorchDynamo/TorchInductor).
Prior experience optimizing performance for low-latency, resource-constrained systems or embedded AI pipelines (e.g. Jetson systems or other edge AI accelerators).

GPU deep learning has provided the foundation for machines to learn, perceive, reason and solve problems posed using human language. The GPU started out as the engine for simulating human imagination, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA's GPU runs deep learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Two modes of the human brain, two modes of the GPU. This may explain why NVIDIA GPUs are used broadly for deep learning, and NVIDIA is increasingly known as “the AI computing company.” Come, join our DL Architecture team, where you can help build a real-time, cost-effective computing platform driving our success in this exciting and quickly growing field.

#LI-Hybrid

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 26, 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.

Apply Now

Refine Your Search

Quantization Transformer Architecture accelerator jobs

Senior Deep Learning Software Engineer, TensorRT Performance

Embedded AI Tooling Engineer

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AI Accuracy Architect

AI Inference Engineer

Lead Compiler Engineer

Principal Engineer/Manager

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AI Compiler and Performance Engineer

Staff Autonomy Engineer

Staff CV Applied Research Engineer, Edge AI

Autonomous Driving Multimodal Model Algorithm Engineer

AI Accelerator Silicon Architect

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