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Freelance Nvidia Machine Learning Jobs (NOW HIRING)

Nvidia

OR · On-site

$104.40K - $143.40K/yr

Now, NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the ... Intelligent machines powered by AI are no longer science fiction. GPU Deep Learning has made it ...

Nvidia

Senior Deep Learning Software Engineer

Santa Clara, CA · Hybrid

$143.90K - $189.70K/yr

Familiarity with NVIDIA's deep learning SDKs such as TensorRT. * Prior experience in writing high-performance GPU kernels for machine learning workloads in frameworks such as CUDA, CUTLASS, or Triton.

Quantiphi, Inc.

OR · On-site

$114.40K - $137.40K/yr

As an Elite/Premier Partner for Google Cloud, AWS, NVIDIA, Snowflake, and others, we've been ... We are looking for a Machine Learning Engineer with strong expertise in Google Cloud AI tools, ML ...

Quantiphi, Inc.

Machine Learning Engineer

$117.20K - $140.70K/yr

As an Elite/Premier Partner for Google Cloud, AWS, NVIDIA, Snowflake, and others, we've been ... We are looking for a Machine Learning Engineer with strong expertise in Google Cloud AI tools, ML ...

Nvidia

Senior Deep Learning Software Engineer

Redmond, WA · Hybrid

$137.20K - $180.90K/yr

Familiarity with NVIDIA's deep learning SDKs such as TensorRT. * Prior experience in writing high-performance GPU kernels for machine learning workloads in frameworks such as CUDA, CUTLASS, or Triton.

Mindrift

Machine Learning Developer (Freelance)

$90/hr

Ideally, contributors will have: * 5+ years of hands-on machine learning experience with proven business impact * Portfolio of completed projects and publications showcasing real-world problem ...

Heven AeroTech

Machine Learning Engineer

Sterling, VA · On-site

Machine Learning Engineer Company: Heven AeroTech Location: Sterling, Virginia FLSA: Exempt About ... Edge hardware deployment (NVIDIA Jetson, Google Coral TPU) * Embedded Linux and ROS experience

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA ...

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

As of May 31, 2026, the average hourly pay for freelance nvidia machine learning in the United States is $47.71, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $61.78 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Freelance Nvidia Machine Learning Engineer, and why are they important?

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 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 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.

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What are the most commonly searched types of Nvidia Machine Learning jobs? The most popular types of Nvidia Machine Learning jobs are:
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Freelance Nvidia Machine Learning jobs near you
Infographic showing various Freelance Nvidia Machine Learning job openings in the United States as of May 2026, with employment types broken down into 98% Full Time, 1% Temporary, and 1% Nights. Highlights an 91% Physical, and 9% Hybrid job distribution, with an average salary of $99,230 per year, or $47.7 per hour.
Senior Machine Learning Engineer, Perception - Autonomous Driving

Senior Machine Learning Engineer, Perception - Autonomous Driving

Nvidia

On-site

$104.40K - $143.40K/yr

Full-time

Posted 14 days ago

Job description

Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. Now, NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world.

We are now looking for an extraordinary Senior Perception Engineer to develop and productize NVIDIA's autonomous driving solutions. As a member of our perception team, you will be driving E2E solutions for perception modules that are responsible for online mapping - including road layouts, lane structures, boundaries, crosswalks, and other traffic components critical for driving without reliance on HD maps. You will be challenged to improve robustness and accuracy as well as efficiency of the solutions to fully enable autonomous driving anywhere and anytime.

What You'll Be Doing:

  • Designing end2end solutions for Perception and AV stack to enable road network detections across various driving environments from complex intersections to rural curvy roads to multi-level highways.

  • Applied research and development of innovative deep learning models for lane graph construction, road boundary detection, traffic element recognition, and other static-world tasks.

  • Develop generalizable approaches to support diverse ODDs and Country/region expansion

  • Drive and prioritize data-driven development by working with large data collection and labeling teams to bring in high value data to improve perception system accuracy. Efforts will include data collection prioritization and planning, labeling prioritization, labeling efficiency optimization, so that value of data is maximized

  • Leverage data simulation and augmentation for solving extreme scenarios

  • Productize the developed perception solutions by meeting product requirements for safety, latency, and SW robustness.

What We Need to See:

  • Minimum Requirement: PhD with 4+ years, MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.

  • 2+ years of technical leadership demonstrating high technical and organizational complexity is a big plus.

  • Hands-on work experience in developing deep learning and algorithms to solve sophisticated real world problems, and proficiency in using deep learning frameworks (e.g., PyTorch).

  • Experience in data-driven development and collaboration with data and ground truth teams.

  • Strong programming skills in python and/or C++.

  • Outstanding communication and teamwork skills as we work as a tightly-knit team, always discussing and learning from each other.

Ways to Stand Out from the Crowd:

  • Proven expertise in developing generalizable perception solutions for autonomous driving or robotics using deep learning with cameras.

  • Hands-on experience in developing and deploying DNN-based solutions to embedded platforms for real time applications.

  • Proven expertise in deep learning backed up by technical publications in leading conferences/journals.

  • Expertise with Transformers, BEV architectures, and modern static-world perception techniques.Experience in working on similar online mapping and complex road detection problems is a big plus.

Intelligent machines powered by AI are no longer science fiction. GPU Deep Learning has made it possible for self-driving cars to learn, perceive, and reason about the world. NVIDIA GPUs power the algorithms that enable both static world understanding and scalable perception across global road systems. Join us and help define the future of reliable, data-driven autonomous driving.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until April 12, 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.
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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