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Volunteering Deep Learning Research Jobs in Renton, WA

Apple

AIML - Machine Learning Research

Seattle, WA

$142K - $263K/yr

As part of this group, you will be doing large scale machine learning and deep learning research and development to improve Open Domain Question Answering (using both structured knowledge graph data ...

Apple Inc.

AIML - Machine Learning Research

Seattle, WA · On-site

$142.30 - $263.30/hr

As part of this group, you will be doing large scale machine learning and deep learning research and development to improve Open Domain Question Answering (using both structured knowledge graph data ...

NVIDIA

Senior Deep Learning Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

They are seeking a Deep Learning Compiler Engineer to analyze deep learning networks and develop ... research experience in performance analysis and compiler optimizations • Ability to work ...

Nvidia

Deep Learning Compiler Engineer

Redmond, WA

... or research experience in compiler optimization, performance analysis and IR design. * Ability to ... MLIR, LLVM, XLA, TVM and deep learning models and algorithms. With highly competitive salaries and ...

New

Nvidia

Senior Deep Learning Compiler Engineer

Redmond, WA

$117K - $160K/yr

... research experience in performance analysis and compiler optimizations. * Ability to work ... MLIR, XLA, TVM, LLVM, deep learning models and algorithms, and deep learning frameworks, such as ...

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Volunteering Deep Learning Research information

What is volunteering deep learning research?

Volunteering deep learning research involves contributing your time and skills to support research projects focused on deep learning, often within academic, nonprofit, or open-source communities. Volunteers may help with tasks such as data annotation, coding, literature reviews, or running experiments. This work can be a great way to gain hands-on experience, collaborate with experienced researchers, and make a positive impact without a formal employment relationship. Opportunities are available for individuals with varying levels of expertise, from students to professionals.

What types of projects and tasks can I expect to work on as a volunteer in deep learning research?

As a volunteer in deep learning research, you may be involved in a variety of tasks such as data preprocessing, literature reviews, implementing and testing machine learning models, or assisting with experiments. Depending on the research lab or team, you could also contribute to writing code, analyzing results, or preparing research papers and presentations. Collaboration is common, so you'll likely work closely with researchers, graduate students, and other volunteers. This role is an excellent opportunity to gain hands-on experience, deepen your understanding of deep learning concepts, and build a network within the AI research community.

What are the key skills and qualifications needed to thrive as a volunteering deep learning researcher, and why are they important?

To thrive as a Volunteering Deep Learning Researcher, you need a strong background in mathematics, programming (especially Python), and foundational knowledge of machine learning concepts, often supported by relevant coursework or self-study. Familiarity with deep learning frameworks such as TensorFlow or PyTorch and version control systems like Git is typically required. Curiosity, collaboration, effective communication, and self-motivation are standout soft skills in this role. These skills and qualities are crucial for contributing meaningfully to research projects, learning independently, and advancing innovative solutions within a team-oriented research environment.

What is the difference between Volunteering Deep Learning Research vs Data Scientist?

AspectVolunteering Deep Learning ResearchData Scientist
CredentialsTypically requires knowledge of deep learning frameworks, programming skills, and research experience; often no formal certification neededRequires degrees in data science, statistics, or related fields; certifications like Certified Data Scientist are common
Work EnvironmentResearch-focused, often nonprofit or academic settings, with flexible hoursCorporate or industry settings, structured work hours, project-driven
Employer & IndustryAcademic institutions, research labs, nonprofitsTech companies, finance, healthcare, and other industries

While both roles involve working with data and machine learning, volunteering deep learning research focuses on academic or nonprofit research projects often without formal compensation, whereas data scientists work in industry settings with a focus on applying data analysis to business problems.

What are popular job titles related to Volunteering Deep Learning Research jobs in Renton, WA?

For Volunteering Deep Learning Research jobs in Renton, WA, the most frequently searched job titles are:

What cities near Renton, WA are hiring for Volunteering Deep Learning Research jobs?

Cities near Renton, WA with the most Volunteering Deep Learning Research job openings:

Volunteering Deep Learning Research jobs near you
Infographic showing various Volunteering Deep Learning Research job openings in Renton, WA as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Senior Applied Deep Learning Research Scientist, Efficiency

NVIDIA

Seattle, WA • On-site

$112K - $142K/yr

Full-time

Re-posted 18 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 246 rated software companies

Job description

Job Summary:
NVIDIA is seeking an Applied Deep Learning Research Scientist to join their ADLR – Efficiency team. The role focuses on improving deep learning efficiency through innovative algorithms, research on neural network architectures, and collaboration across various teams to optimize AI technologies.
Responsibilities:
• Research of low-bit number representations and pruning and their effect on neural network inference and training accuracy. This includes requirements by the existing state of art neural networks, as well as co-design of future neural network architectures and optimizers.
• Innovate with new algorithms to make deep learning more efficient while retaining accuracy, and open-source or publish these algorithms for the world to use.
• Run large-scale deep learning experiments to prove out ideas and analyze the effects of efficiency improvements.
• Collaborate across the company with teams making the hardware, software and deep learning architectures.
Qualifications:
Required:
• PhD degree in AI, computer science, computer engineering, math or a related field or equivalent experience in some of the areas listed below can substitute for an advanced degree.
• 5+ years of relevant industrial research experience.
• Familiarity with state-of-art neural network architectures, optimizers and LLM training.
• Experience with modern DL training frameworks and/or inference engines.
• Fluency in Python, and solid coding/software-engineering practices.
• A proven track-record in publications and/or the ability to run large-scale experiments.
• A strong interest in neural network efficiency.
Preferred:
• Experience in quantization, pruning, numerics and efficient architectures.
• A background in computer architecture.
• Experience with GPU computing, kernels, CUDA programming and/or performance analysis.
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. 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

Year founded

1993

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