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Deep Learning Semiconductor Engineer Jobs (NOW HIRING)

Staff Deep Learning Engineer

Columbia, MD · On-site

$185K - $235K/yr

Overview We are seeking a Staff Deep Learning Research Engineer to design, build, and train novel neural network architectures that solve hard problems across Quidient's GSR platform. This is not an ...

Staff Deep Learning Engineer

Columbia, MD · On-site

$185K - $235K/yr

Overview We are seeking a Staff Deep Learning Research Engineer to design, build, and train novel neural network architectures that solve hard problems across Quidient's GSR platform. This is not an ...

Senior Deep Learning Engineer

Austin, TX · On-site +1

$130K - $180K/yr

We're hiring 3 Senior Deep Learning Engineers to join our Neural Networks team. Your primary focus will be optimizing neural networks to efficiently run on our hardware and building a model ...

Intern, Deep Learning Engineer

Houston, TX · On-site

$14.25 - $19/hr

Train, tune, and optimize deep learning models using our large-scale compute clusters and truck ... Engineering Plus: Experience with Linux, Git, C++, or deployment tools like TensorRT/ONNX.

Intern, Deep Learning Engineer

Houston, TX

$14.25 - $19/hr

Train, tune, and optimize deep learning models using our large-scale compute clusters and truck ... Engineering Plus: Experience with Linux, Git, C++, or deployment tools like TensorRT/ONNX.

About the Role As a Staff Deep Learning Engineer in the Deep Learning team at Hayden, you are a technical anchor for the team - able to own and deliver complex, long-horizon perception projects while ...

We are hiring software engineers for the Tensor IR & CUDA Tile team. NVIDIA GPUs are at the center of the deep learning revolution and continue to enable breakthroughs in generative AI, large ...

We are hiring software engineers for the Tensor IR & CUDA Tile team. NVIDIA GPUs are at the center of the deep learning revolution and continue to enable breakthroughs in generative AI, large ...

We're looking for a Deep Learning Field Engineer to operate at the forefront of CV deployment in industry - building best-in-class CV systems that leverage deep learning techniques to solve a broad ...

We are hiring software engineers for the Tensor IR & CUDA Tile team. NVIDIA GPUs are at the center of the deep learning revolution and continue to enable breakthroughs in generative AI, large ...

Senior Deep Learning Engineer - Perception

San Jose, CA · On-site

$123K - $169K/yr

Description Senior Deep Learning Engineer, Computer Vision imagry.E4.E30@comeetapply.com Location: San Jose, CA , On Site We are looking for a capable and experienced Sr. Deep Learning Engineer to ...

Showing results 21-40

Deep Learning Semiconductor Engineer information

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$15

$34

$54

How much do deep learning semiconductor engineer jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for deep learning semiconductor engineer in the United States is $34.09, according to ZipRecruiter salary data. Most workers in this role earn between $24.04 and $40.87 per hour, depending on experience, location, and employer.

What are popular job titles related to Deep Learning Semiconductor Engineer jobs?

For Deep Learning Semiconductor Engineer jobs, the most frequently searched job titles are:

Infographic showing various Deep Learning Semiconductor Engineer job openings in the United States as of June 2026, with employment types broken down into 6% Full Time, 85% Part Time, 3% Temporary, and 6% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $70,911 per year, or $34.1 per hour.

Performance Engineer - Deep Learning

Santa Clara, CA • On-site

NVIDIA
Computer and Electronic Product Manufacturing • 10K+ employees

Full-time

Re-posted 17 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz


Job description

Job Summary:
NVIDIA is hiring software engineers to build and optimize tools for Deep Learning engineers globally. This role involves optimizing performance for Deep Learning models on NVIDIA GPUs and collaborating with various teams to enhance AI applications.
Responsibilities:
• Optimize the performance of Deep Learning models for NVIDIA GPUs and systems.
• Study and tune Deep Learning training workloads at large scale.
• Optimize production AI models used by enterprise customers and partners.
• Build and support NVIDIA submissions to community benchmarks like MLPerf.
• Optimize the performance of influential, contemporary models coming out of academic and industry research, for NVIDIA GPUs and systems.
• Deliver the benefits of NVIDIA’s latest hardware and platform software innovations to the Deep Learning community.
• Inform design of new hardware generations, and core platform software components for NVIDIA GPUs and systems.
Qualifications:
Required:
• BS or equivalent experience in Computer Science, Electrical Engineering or a related field.
• 2+ years of experience with C++ and Python programming.
• Strong background with parallel programming, preferably on GPUs.
• Knowledge of Computer Architecture and/or Operating Systems.
• Proven experience developing large software projects.
• Excellent verbal and written communication skills.
Preferred:
• Experience in PyTorch, Tensorflow or MXNet.
• Background with performance analysis and profiling of workloads.
• Participation in the open source community.
• Proven experience working with multidisciplinary teams.
Company:
NVIDIA designs graphics processing units and accelerated computing hardware for AI and high-performance computing applications. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US