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Freelance Nvidia Machine Learning Jobs (NOW HIRING)

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 ...

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 ...

Prosum Inc.

Machine Learning Engineer

Phoenix, AZ · On-site

$130K - $150K/yr

Evaluate and implement performance improvements using NVIDIA GPU technologies and profiling tools. Model Deployment & Optimization * Optimize, quantize, and deploy machine learning models using ...

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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 Sep 10, 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 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 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 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 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 September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $99,230 per year, or $47.7 per hour.

Machine Learning Engineer - Autonomy

Sterling, VA • On-site

Heven AeroTech
See more jobs at Heven AeroTechexternal

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 20 days ago

Job description

Title: Machine Learning Engineer, Autonomy
Company: Heven AeroTech
Location: Bingen, Washington or Sterling, Virginia
FLSA: Exempt
About Our Company:
At Heven AeroTech (Heven), we don't just believe in the power of people-we build our success on it. As a recognized leader in hydrogen-powered drones, we've earned recognition for creating a workplace where innovation thrives, collaboration is second nature, and every employee feels valued. Our culture is anchored in trust and a shared commitment to excellence.
We believe great teams are built on individuals who are humble, hungry, and smart-those who put team success first, take initiative to continuously improve, and demonstrate strong interpersonal awareness. At Heven, your voice matters, your ideas are heard, and your contributions make a tangible impact as you grow through hands-on experience and collaboration across the team.
Role Summary:
Reporting to the Head of Mission Systems and Software, the Machine Learning Engineer - Autonomy develops and deploys machine learning and autonomy capabilities for Heven AeroTech uncrewed aircraft systems. The role focuses on practical UAS autonomy, including perception, tracking, sensor fusion, mission-level decision making, planning, and integration with flight-control, mission-system, onboard-compute, and payload interfaces. This engineer works closely with other Machine Learning Engineers, Platform Engineers, Flight Test, and aircraft engineering teams to take autonomy capabilities from development through simulation, integration, ground test, and flight test.
Essential Responsibilities:
  • Develop, integrate, and deploy machine learning and autonomy capabilities for uncrewed aircraft, with emphasis on reliable operation on real aircraft and onboard compute.
  • Develop mission-level autonomous behaviors using appropriate combinations of state machines, behavior trees, planners, optimization methods, deterministic logic, and machine learning.
  • Develop and integrate perception capabilities including object detection, classification, tracking, scene understanding, sensor fusion, and geospatial reasoning.
  • Integrate autonomy software with autopilots, companion computers, mission computers, sensors, payloads, data links, and GCS/C2 systems while maintaining clear interfaces with flight-control functions.
  • Develop production-quality C++ and Python software for real-time and near-real-time execution, including optimization for NVIDIA GPU and embedded edge-compute platforms.
  • Develop and use simulation, SIL, HIL, bench-test, and automated test environments to evaluate autonomy behavior and reduce risk prior to flight.
  • Support aircraft integration, ground test, and flight test of autonomy capabilities, including analysis of logs and test data to characterize performance and drive improvements.
  • Collaborate across Heven AeroTech with Machine Learning Engineers, Platform Engineers, Flight Test, avionics, electrical, mechanical, and other engineering teams.

Qualifications & Experience:
Required:
  • BA/BS degree in Computer Science, Electrical Engineering, Robotics, Aerospace Engineering, or a related technical field, or equivalent practical experience.
  • 2-5 years of experience developing and deploying machine learning or autonomy software on robotic, autonomous, or UAS platforms.
  • Strong C++ and Python development skills, including Linux-based development and modern machine learning frameworks.
  • Working knowledge of perception, sensor integration, autonomous decision making or planning, and real-time system integration.
  • Professional working proficiency in English (spoken and written) is required to perform the responsibilities of this role.

Preferred:
  • Direct experience with UAS autonomy, aircraft integration, or flight test.
  • Experience with NVIDIA edge compute, CUDA/TensorRT, ROS 2, MAVLink, or comparable robotics and vehicle interfaces.
  • Aerospace or defense experience and eligibility to obtain a DoD Secret clearance.

Physical Requirements:
  • Ability to work effectively in a standard office, engineering laboratory, aircraft integration, hangar, and outdoor flight-test environment.
  • Ability to stand, walk, bend, kneel, reach, and work around aircraft, ground-support equipment, test equipment, and computing hardware for extended periods as required.
  • Ability to lift, carry, and position equipment and components weighing up to 25 pounds, with or without reasonable accommodation.
  • Ability to safely work in outdoor environments and varying weather conditions during ground and flight-test activities.
  • Ability to work around aircraft systems, electrical equipment, rotating equipment, batteries, and other laboratory/flight-test hazards while following applicable safety procedures and PPE requirements.
  • Ability to visually inspect equipment, read computer displays, instrumentation, schematics, logs, and test data, with or without reasonable accommodation.
  • Ability to work flexible hours, including early mornings, evenings, or occasional weekends, when required to support aircraft integration, ground testing, or flight-test operations.
  • Ability and willingness to travel to company facilities, customer sites, and/or designated flight-test locations as required by the position.

Benefits Overview:
Heven AeroTech offers a competitive benefits package designed to support the health, financial security, and overall well-being of our employees and their families. Benefits include medical, dental, and vision coverage, retirement plans, paid time off/sick, and additional protections such as critical illness, hospital indemnity, accident coverage, and short- and long-term disability.
Equal Employment Opportunity Statement:
Heven AeroTech is an Equal Opportunity Employer and considers all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic under applicable law.
Budgeted Salary Range:
$110,000-$165,000 USD

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