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Nvidia Machine Learning Internship Jobs in Seattle, WA

Orchard Robotics

Machine Learning Engineer

Seattle, WA · On-site

$135K - $210K/yr

We are looking for a Machine Learning Engineer to build creative, practical, and robust solutions ... Experience deploying & optimizing ML models to run fast on embedded compute like NVIDIA Jetson

Orchard Robotics

Machine Learning Engineer

Seattle, WA · On-site

$135K - $210K/yr

We are looking for a Machine Learning Engineer to build creative, practical, and robust solutions ... Experience deploying & optimizing ML models to run fast on embedded compute like NVIDIA Jetson

Orchard

Machine Learning Engineer

Seattle, WA · On-site

$120 - $190/hr

We are looking for a Machine Learning Engineer to build creative, practical, and robust solutions ... Experience deploying & optimizing ML models to run fast on embedded compute like NVIDIA Jetson

Nvidia

Senior Solutions Architect

Seattle, WA

We are looking for a networking savvy Solutions Architect to join the NVIDIA team focused on supporting accelerated networking for AI, Machine Learning, and HPC. As part of the NVIDIA Solutions ...

Nvidia

Senior Deep Learning Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

... interns is a bonus. With highly competitive salaries and a comprehensive benefits package, NVIDIA ... Learning and Autonomous Vehicles. Your base salary will be determined based on your location ...

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 ... and interns is a bonus Company : NVIDIA is a computing platform company operating at the ...

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Nvidia Machine Learning Internship information

See Seattle, WA salary details

$29K

$48.5K

$100.1K

How much do nvidia machine learning internship jobs pay per year?

As of Aug 14, 2026, the average yearly pay for nvidia machine learning internship in Seattle, WA is $48,461.00, according to ZipRecruiter salary data. Most workers in this role earn between $37,000.00 and $52,300.00 per year, depending on experience, location, and employer.

What types of projects do interns typically work on during the Nvidia machine learning internship?

During the Nvidia Machine Learning Internship, interns often work on real-world projects involving deep learning, computer vision, or natural language processing. These projects may include developing new models, optimizing existing algorithms, or contributing to open-source frameworks. Interns typically collaborate with experienced engineers and researchers, gaining hands-on experience while having access to state-of-the-art GPU hardware. The work environment encourages innovation and learning, and interns are often given opportunities to present their results to senior team members.

What is the difference between Nvidia Machine Learning Internship vs Data Science Internship?

AspectNvidia Machine Learning InternshipData Science Internship
Required CredentialsRelevant coursework, programming skills, possibly some machine learning certificationsStatistics, programming, data analysis skills, often a related degree
Work EnvironmentResearch labs, tech company offices, collaborative teams focused on AI/ML projectsBusiness environments, data analysis teams, cross-functional collaboration
Employer & Industry UsageTech companies, AI/ML research labs, hardware/software firms like NvidiaVarious industries including tech, finance, healthcare, and consulting

While both internships involve working with data and programming, Nvidia Machine Learning Internships focus specifically on developing and optimizing machine learning models in a hardware and AI context, whereas Data Science Internships emphasize analyzing data to derive insights across diverse industries.

What is an Nvidia machine learning internship?

An Nvidia Machine Learning Internship is a temporary, hands-on program for students or recent graduates to work with Nvidia’s teams on projects related to machine learning and artificial intelligence. Interns typically assist with research, data analysis, model development, and software engineering tasks using Nvidia’s cutting-edge GPU technologies. The internship provides valuable real-world experience, mentorship from industry experts, and the opportunity to contribute to innovative AI solutions. It’s a great way to build skills, expand your professional network, and potentially secure a full-time role at Nvidia in the future.

What are the key skills and qualifications needed to thrive as an Nvidia machine learning intern, and why are they important?

To excel as an Nvidia Machine Learning Intern, you need a solid foundation in computer science, mathematics, and machine learning concepts, typically supported by progress toward a relevant degree. Familiarity with programming languages like Python, deep learning frameworks such as TensorFlow or PyTorch, and GPU computing tools (e.g., CUDA) is essential. Strong analytical thinking, problem-solving skills, and effective teamwork set standout interns apart. These competencies enable you to contribute meaningfully to advanced AI projects and collaborate efficiently within Nvidia's innovative environment.

What are the most commonly searched types of Nvidia Machine Learning jobs in Seattle, WA?

The most popular types of Nvidia Machine Learning jobs in Seattle, WA are:

What are popular job titles related to Nvidia Machine Learning Internship jobs in Seattle, WA?

For Nvidia Machine Learning Internship jobs in Seattle, WA, the most frequently searched job titles are:

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The top searched job categories for Nvidia Machine Learning Internship jobs in Seattle, WA are:

Nvidia Machine Learning Internship jobs near you

Machine Learning Engineer

Orchard Robotics

Seattle, WA • On-site

$135K - $210K/yr

Full-time

Medical, Dental, Vision

Re-posted 3 days ago

Job description

Orchard Robotics is a Series A startup backed by top VCs like Quiet Capital, Shine Capital, and General Catalyst. We're securing America's food supply by building the AI farmer that automates our nation's farms. We've raised over $25M in pursuit of our mission to help farmers farm more profitably and sustainably than ever before.
What We Do:
We start by building AI-powered camera systems that collect the most valuable data for farmers, telling them everything about what is growing on their millions of trees, vines, and plants, across thousands of acres of farmland.
Our state-of-the-art AI analyzes every one of the billions of fruit across a farm. We provide accurate yield estimates, fruit counts, size projections, disease detection, inventories, bloom maps, and more! All this data lives in our cloud platform, FruitScope OS, that we've developed from the ground up to enable farmers to manage their crop with precision.
Today, our technology is trusted by some of the largest farms in the nation. We are growing fast, and have the industry-leading product. Farmers use our software every day to make critical decisions and run more efficient, profitable operations.
The Role:
In order to analyze billions of fruit on farms all year long, our advanced, tractor-mounted camera systems have to know a.) precisely where they are, and b.) everything about the fruit they are seeing.
We are looking for a Machine Learning Engineer to build creative, practical, and robust solutions to ML/CV software and infrastructure problems, relating to training edge ML models on massive amounts of real-world farm image data collected by our camera systems.
About the role:
  • Full-time, in-person role at our San Francisco or Seattle office.
  • As an early engineer, you'll receive generous equity compensation
  • Comprehensive Health, Vision, and Dental coverage, and we cover 100% of the premium
  • We move fast, and sometimes this means staying late or working weekends
  • Our team is close-knit & highly driven, you'll work directly with our CEO and entire team
  • We're deeply motivated by the impact we're making - every line of code written or new system built means less food that goes to waste, and more people who are fed.

What you'll do:
  • Build and maintain scalable ETL pipelines for processing large, diverse image datasets collected from our tractor-mounted camera systems in farms.
  • Develop and deploy infrastructure for model training, evaluation, and inference, both in the cloud and on edge devices.
  • Design and implement intelligent active sampling infrastructure to optimize data collection and improve model performance.
  • Stay up-to-date with current literature in computer vision models and architectures, and apply relevant advancements to our systems.
  • Collaborate with a multidisciplinary team to integrate ML solutions into production robotics systems.
  • Work closely with agronomists and farmers to understand crop biology and translate domain knowledge into actionable ML features.
  • Be a generalist, supporting different parts of our software stack as needed.

What makes you a good fit:
  • 2+ years of real-world, industry experience building production-grade data pipelines and ML infrastructure.
  • Proficiency in Python and experience with ML frameworks (e.g., PyTorch).
  • Strong experience with data engineering tools (e.g., Pandas, SQL, MLFlow, WandB).
  • Familiarity with cloud platforms (AWS, GCP) and containerization (Docker, Kubernetes).
  • Experience working with massive amounts of real-world training data.
  • Familiarity with MLops software and data engineering to ensure consistent deployment of ML models.
  • Ability to work independently, learn quickly, and operate in a dynamic environment
  • Enthusiasm for taking on multiple roles and responsibilities as our company grows.

Bonus Points:
  • Experience deploying & optimizing ML models to run fast on embedded compute like NVIDIA Jetson
  • Experience prototyping, evaluating, or deploying new ML/CV models on the edge.

If you're looking to help make a positive impact in the world by building the future of farming, come join us!

Apply