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Deep Learning Engineer Intern Jobs (NOW HIRING)

NVIDIA AI

Senior Deep Learning Engineer

Redmond, WA · On-site

$62 - $79.75/hr

They are seeking an ambitious and forward-thinking senior deep learning engineer to contribute to the development of next-generation inference optimizations targeting frontier workloads including ...

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Nvidia

Senior Deep Learning Engineer

Santa Clara, CA · On-site

$65 - $83.75/hr

We are now looking for a Senior Deep Learning Engineer!At NVIDIA, we are at the forefront of advancing the capabilities of artificial intelligence. We are seeking an ambitious and forward-thinking ...

Nvidia

Senior Deep Learning Engineer

Redmond, WA · On-site

$62 - $79.75/hr

We are now looking for a Senior Deep Learning Engineer!At NVIDIA, we are at the forefront of advancing the capabilities of artificial intelligence. We are seeking an ambitious and forward-thinking ...

Syntiant

Model Converter Engineer Intern

Irvine, CA · On-site

$18 - $23.25/hr

As a Model Converter Engineer Intern , you will be responsible for developing solutions that meet ... Syntiant's advanced chip solutions merge deep learning with semiconductor design to produce ultra ...

Syntiant

Model Converter Engineer Intern

Irvine, CA · On-site

$18 - $23.25/hr

As a Model Converter Engineer Intern , you will be responsible for developing solutions that meet ... Syntiant's advanced chip solutions merge deep learning with semiconductor design to produce ultra ...

Syntiant

Model Converter Engineer Intern

Irvine, CA

$18 - $23.25/hr

As a Model Converter Engineer Intern , you will be responsible for developing solutions that meet ... Syntiant's advanced chip solutions merge deep learning with semiconductor design to produce ultra ...

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

As of May 30, 2026, the average hourly pay for deep learning engineer intern in the United States is $17.04, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What is the difference between Deep Learning Engineer Intern vs Machine Learning Engineer Intern?

AspectDeep Learning Engineer InternMachine Learning Engineer Intern
Required CredentialsTypically pursuing or holding a degree in Computer Science, Data Science, or related fields; familiarity with deep learning frameworksSimilar educational background; knowledge of machine learning algorithms and programming skills
Work EnvironmentResearch labs, tech companies, startups focusing on neural networks and AI modelsBroader industry settings including finance, healthcare, and tech, working on various ML models
Employer & Industry UsageUsed in companies developing AI products, autonomous systems, and advanced neural network applicationsApplied across industries for predictive analytics, data modeling, and automation tasks

While both roles involve machine learning concepts, a Deep Learning Engineer Intern specializes in neural networks and deep learning frameworks, whereas a Machine Learning Engineer Intern works on a wider range of algorithms and models across various industries.

What cities are hiring for Deep Learning Engineer Intern jobs? Cities with the most Deep Learning Engineer Intern job openings:
What are the most commonly searched types of Deep Learning Engineer jobs? The most popular types of Deep Learning Engineer jobs are:
What states have the most Deep Learning Engineer Intern jobs? States with the most job openings for Deep Learning Engineer Intern jobs include:
Deep Learning Engineer Intern jobs near you
Deep Learning Research Intern

Deep Learning Research Intern

Futurewei Technologies, Inc.

San Jose, CA • On-site

$18 - $59/hr

Internship

Posted 3 days ago

Job description

Deep Learning Research Intern
(Embodied AI, Multimodal Foundation Models & Efficient Systems)
About Us
Futurewei is a well-funded independent research organization with a long history of R&D innovation in Silicon Valley. We are committed to open-source development, fundamental research, and advancing next-generation intelligent systems through collaboration and standards development.
About the Role
We are seeking a strong deep learning research intern to join our ASID team in San Jose, CA. This role focuses on building learning systems for embodied intelligence, emphasizing how multimodal foundation models can be trained, compressed, and deployed efficiently in embodied and interactive environments.
Our work goes beyond static perception. We study intelligence grounded in embodied experience-the interaction of perception, action, and environment over time-while ensuring models remain efficient, scalable, and deployable in real-world systems.
Core Research Focus Areas
The intern will contribute to one or more of the following interconnected research directions:
1. Multimodal Foundation Models
  • Fine-tuning and adaptation of large language models (LLMs), vision-language models (VLMs), and vision-language-action (VLA) models
  • Multimodal representation learning across vision, language, and action
  • Grounding foundation models in embodied experience and temporal interaction

2. Neural (Generative) Image and Video Compression
  • Learning-based image and video compression models
  • Efficient visual representations for perception and downstream embodied tasks
  • Joint optimization of compression efficiency, reconstruction quality, and task relevance

3. Embodied AI
  • Learning frameworks that couple perception, action, and environment dynamics
  • World models, predictive learning, and agent-centric representations
  • Embodied learning in simulation or real-world-inspired environments

4. Model Compression & Inference Acceleration for Embodied Systems
  • Model compression, pruning, quantization, and distillation
  • Efficient inference and deployment strategies for embodied and real-time applications
  • Hardware- and system-aware optimization for edge or robotic platforms

Responsibilities
  • Conduct research in one or more of the focus areas above
  • Design and implement learning algorithms and experimental pipelines
  • Develop prototype systems or demos for embodied and multimodal AI applications
  • Collaborate closely with researchers in a fast-paced, research-driven environment

Qualifications
  • MS or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, Robotics, Mathematics, or a related field
  • Strong foundation in machine learning and deep learning
  • Experience or strong interest in multimodal models, embodied AI, compression, or efficient inference
  • Proficiency with PyTorch; experience with HuggingFace or similar frameworks is a plus
  • Solid Python programming skills
  • Research experience with publications in top conferences or journals preferred
  • Strong communication skills and ability to work effectively in a global research team

Location: San Jose, CA
Hourly interns pay range: $18 to $59, depending on degree-seeking academic program (PhD, Master's, Bachelor's, etc.), years of relevant experience, year in school, geographic location, credentials, qualifications, and other job-related factors.
Housing allowance and relocation benefit might be provided to intern candidates who meet the qualifications. Additional details on the compensation package will be provided to candidates during the interview process.
Futurewei Technologies, Inc. is proud to be an Equal Opportunity Employer.
All qualified applicants will receive consideration for employment without regard to race, color, gender, sexual orientation, gender identity or expression, religion, national origin, marital status, age, disability, veteran status, genetic information, or any other protected status under federal, state, and local laws.

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