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Nvidia Machine Learning Internship Jobs in Virginia

The Role As a Senior Machine Learning Engineer, you will turn cutting-edge AI/ML research into ... Experience running models on NVIDIA GPUs * Experience containerizing and deploying software using ...

The Role As a Senior Machine Learning Engineer, you will turn cutting-edge AI/ML research into ... Experience running models on NVIDIA GPUs * Experience containerizing and deploying software using ...

The Role As a Senior Machine Learning Engineer, you will turn cutting-edge AI/ML research into ... Experience running models on NVIDIA GPUs * Experience containerizing and deploying software using ...

The Role As a Senior Machine Learning Engineer, you will turn cutting-edge AI/ML research into ... Experience running models on NVIDIA GPUs * Experience containerizing and deploying software using ...

Senior Machine Learning Engineer

Mclean, VA · On-site

$105K - $145K/yr

Senior Machine Learning Engineer Location: McLean, VA (hybrid); occasional travel to Durham, NC and ... Experiment tracking, Docker, ONNX/TensorRT, deploying inference services to the edge (e.g., NVIDIA ...

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Lead Machine Learning Engineer

Mclean, VA · On-site

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Lead Machine Learning Engineer

Mclean, VA · On-site

$197.30 - $225.10/hr

## Lead Machine Learning EngineerApplylocations: McLean, VAtime type: Full timeposted on: Posted ... Internship experience does not apply)* At least 4 years of experience programming with Python ...

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Lead Machine Learning Engineer

Mclean, VA · On-site

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Lead Machine Learning Engineer

Mclean, VA · On-site

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

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Nvidia Machine Learning Internship information

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 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 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 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 are the most commonly searched types of Nvidia Machine Learning jobs in Virginia?

The most popular types of Nvidia Machine Learning jobs in Virginia are:

What job categories do people searching Nvidia Machine Learning Internship jobs in Virginia look for?

The top searched job categories for Nvidia Machine Learning Internship jobs in Virginia are:

Machine Learning Engineer - Autonomy

Heven AeroTech

Sterling, VA

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 5 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.