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Freelance Nvidia Machine Learning Jobs (NOW HIRING)

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NVIDIA's deep learning and HPC platforms have made a huge impact in various fields and are broadly ... Work with some of the brightest minds in a premier AI company to develop leading machine learning ...

Mindrift

Freelance Machine Learning Engineer

$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 ...

Machina Labs

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

Backed by Lockheed Martin, Toyota, and NVIDIA, we're building the manufacturing infrastructure that ... We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of ...

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

As of May 29, 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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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.
Principal Machine Learning Engineer, Accelerated Apache Spark

Principal Machine Learning Engineer, Accelerated Apache Spark

NVIDIA

Santa Clara, CA • On-site

Full-time

Posted 8 days ago

Job description

Job Summary:
NVIDIA is looking for a Machine Learning Engineer to join the GPU accelerated Apache Spark team. This role involves designing and implementing machine learning solutions to optimize Apache Spark workloads on GPUs and collaborating with partners to deploy complex ML solutions.
Responsibilities:
• Design and implement machine learning solutions for performance prediction and optimization of GPU accelerated enterprise Apache Spark workloads.
• Develop advanced algorithms and adaptive systems to continuously improve the performance of Apache Spark workloads on GPUs.
• Develop AI-based agents and tools to assist with fixing system issues and application optimization.
• Collaborate with key partners and customers on the deployment of complex machine learning solutions in various environments.
• Maintain deep domain expertise by knowing the latest published advances in ML systems and algorithms.
• Provide technical mentorship and leadership in data science and machine learning to a team of engineers.
Qualifications:
Required:
• BS, MS, or PhD or equivalent experience in Machine Learning, Data Science, Computer Science or a closely related field.
• 12+ years of professional experience in designing, implementing, and productionizing high-quality ML/DL solutions.
• 5+ experience as technical lead in ML model development.
• Proven hands-on experience (2+ years) with large-scale data processing platforms, such as Apache Spark.
• Proven ability to employ modern tooling and sound techniques for all aspects of crafting, deploying, and maintaining machine learning models.
• Excellent programming skills in Python and Python data science related libraries like numpy, pandas, scikit-learn, scipy, pytorch, and tensorflow.
• Deep experience with sophisticated ML methodologies, including LLM/GenAI, reinforcement learning, and adaptive, on-line ML systems.
• Strong expertise in feature engineering, feature importance assessment, and developing boosted tree model solutions (e.g., XGBoost).
Preferred:
• Understanding of the internal workings and architecture related to Apache Spark.
• Familiarity with NVIDIA GPUs and CUDA.
• Experience coding in Scala, Java, and/or C++.
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.
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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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