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Freelance Nvidia Machine Learning Jobs in Seattle, WA

Nvidia

Senior Compiler Engineer - AI

Redmond, WA

$137K - $180K/yr

The ideal candidate brings broad experience across machine learning, including reinforcement ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work ...

Nvidia

Senior Robotics Research Scientist

Seattle, WA · On-site

$112K - $142K/yr

... NVIDIA products that will have real-world impact; * Mentoring interns and more junior research scientists and engineers. What we need to see: * A PhD in Robotics, Machine Learning, Computer Science ...

Orchard Robotics

Machine Learning Engineer

Seattle, WA · On-site

$135K - $210K/yr

  • Medical

  • Dental

  • Vision

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

  • Medical

  • Dental

  • Vision

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

  • Medical

  • Dental

  • Vision

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

Apple

Senior / Staff Machine Learning Engineer

Seattle, WA

$175K - $308K/yr

  • Medical

  • Dental

  • Retirement

Ray Data, NVIDIA DALI, WebDataset, or Mosaic StreamingDataset Performance engineering for I/O-bound ... machine learning, with hands-on experience across the end-to-end ML workflow - including data ...

Nvidia

Senior Solutions Architect

Seattle, WA · On-site

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 ...

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Freelance Nvidia Machine Learning information

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How much do freelance nvidia machine learning jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for freelance nvidia machine learning in Seattle, WA is $54.29, according to ZipRecruiter salary data. Most workers in this role earn between $27.64 and $70.29 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a freelance Nvidia machine learning specialist?

To thrive as a Freelance Nvidia Machine Learning Engineer, you need a strong background in machine learning principles, deep learning frameworks (such as TensorFlow or PyTorch), and proficiency in Python programming, often supported by a relevant degree or certifications. Familiarity with Nvidia hardware (GPUs), CUDA programming, and tools like Nvidia Deep Learning SDKs is essential for optimizing and deploying models efficiently. Exceptional problem-solving, self-management, and client communication skills help you deliver effective solutions and maintain successful freelance relationships. Mastery of these skills ensures you can build high-performance models, meet client expectations, and stay competitive in the rapidly evolving ML landscape.

What is the difference between Freelance Nvidia Machine Learning vs Freelance Data Scientist?

AspectFreelance Nvidia Machine LearningFreelance Data Scientist
Required CredentialsKnowledge of Nvidia GPU architectures, CUDA programming, machine learning frameworksStatistics, programming, data analysis skills, often with similar certifications
Work EnvironmentProject-based, remote, often with tech companies or startupsProject-based or consulting, remote or on-site, across various industries
Industry UsageAI, deep learning, GPU-accelerated applicationsData analysis, predictive modeling, business insights

Freelance Nvidia Machine Learning specialists focus on GPU-accelerated AI projects using Nvidia technologies, while Freelance Data Scientists handle broader data analysis and modeling tasks. Both roles are in high demand for tech-driven projects but differ in technical focus and tools used.

What are some common challenges freelance Nvidia machine learning specialists face when working with clients remotely?

Freelance Nvidia Machine Learning specialists often encounter challenges such as ensuring compatibility between client hardware and Nvidia GPU requirements, effectively communicating technical needs and project progress to non-expert clients, and managing project timelines without in-person oversight. Additionally, freelancers may need to set up secure access to client data or cloud environments, which can require extra coordination. Proactively clarifying expectations, maintaining clear documentation, and staying current with Nvidia's latest tools (like CUDA, cuDNN, or TensorRT) are essential strategies for overcoming these challenges.

What does a freelance Nvidia machine learning specialist do?

A Freelance Nvidia Machine Learning specialist is an independent contractor who uses Nvidia hardware and software platforms, such as CUDA and TensorRT, to develop, optimize, and deploy machine learning models. These professionals often work with clients to accelerate AI workloads, implement deep learning solutions, and leverage GPU computing for data processing tasks. Their projects may include computer vision, natural language processing, or other AI applications that benefit from Nvidia’s technology stack. Freelancers in this field need strong programming skills, familiarity with Nvidia SDKs, and experience optimizing models for high-performance computing environments.

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:

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

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Freelance Nvidia Machine Learning jobs near you

Senior Deep Learning Engineering - Autonomous Vehicles

Nvidia

Redmond, WA • On-site

$117K - $160K/yr

Full-time

Re-posted yesterday

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 244 rated software companies

Job description

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. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

At NVIDIA, we're building the future of autonomous driving - from the silicon to the full-stack AI systems that power next-generation robots on wheels. Our ability to deliver safe, scalable autonomy depends on one thing above all: Data. Extensive, diverse, high-quality data. We are seeking a highly skilled Deep Learning Engineer to develop systems and algorithms extracting intelligence from petascale fleets. This role offers an opportunity to build the data engine powering one of the world's most advanced AI platforms. We are looking for hands-on experience training and deploying Large Language Models (LLMs) and Vision-Language Models (VLMs) in production environments. You will collaborate with other researchers, software engineers to bring pioneering AI models from prototype to production.

What you will be doing:

  • Explore SOTA LLM/VLM models for search and classification of AV scenarios

  • Hands on model developments such as fine-tuning large LLM/VLMs for internal use cases

  • Collaborate with software engineers and researchers to ensure seamless integration of models from training to deployment.

What we want to see:

  • Master's or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related field (or equivalent experience)

  • 10+ years of professional experience in deep learning or applied machine learning.

  • Strong foundation in deep learning algorithms, including hands-on experience with LLMs and VLMs

  • Deep understanding of general transformer architectures, inference bottlenecks, and popular model architectures such Qwen family.

  • Proficient in building and deploying models using PyTorch in production-grade environments.

  • Solid programming skills in Python

Ways to stand out from the crowd:

  • Proven experience deploying LLMs or VLMs at scale in real-world applications using vLLM, SGLang.

  • Hands-on experience with SFT, DPO, GRPO techniques for fine-tuning

  • Proven experience in developing image and video search solutions at scale.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 18, 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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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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