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Nvidia Machine Learning Internship Jobs in Houston, TX

Deloitte

Oracle Gen AI Manager

Houston, TX · On-site

... machine learning initiatives * Identify high-value AI use cases and guide teams on prompt ... Experience with LangChain, LangGraph, NVIDIA NIM, or Hugging Face * Experience leading AI or ERP ...

Citadel

Software Engineer - Intern (US)

Houston, TX · On-site

$4.5K - $5.8K/wk

... machine learning and more. As an intern, you'll get to challenge the impossible in technology ... In addition to weekly pay, interns may be eligible for a highly competitive sign-on bonus, housing ...

ConocoPhillips

Intern, Trading Analytics 2027

Houston, TX · On-site

$14.25 - $19/hr

... or machine learning techniques to improve forecasting accuracy for fundamentals or price ... Available for internship start mid-late May 2027 * A minimum of ten (10) continuous weeks ...

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Nvidia Machine Learning Internship information

See Houston, TX salary details

$24.4K

$40.7K

$84K

How much do nvidia machine learning internship jobs pay per year?

As of Aug 20, 2026, the average yearly pay for nvidia machine learning internship in Houston, TX is $40,666.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,000.00 and $43,900.00 per year, depending on experience, location, and employer.

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 Houston, TX?

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For Nvidia Machine Learning Internship jobs in Houston, TX, the most frequently searched job titles are:

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Nvidia Machine Learning Internship jobs near you

Software Engineer, Autonomous Driving Platforms

Bot Auto

Houston, TX • On-site

Full-time

Posted 26 days ago

Job description

About the Role
At Bot Auto, we are revolutionizing the transportation of goods through autonomous trucking. With the agility of a startup and the experience of a team that has achieved numerous industry firsts, we build technology that connects autonomous vehicles, cloud infrastructure, data, machine learning, and real-world fleet operations.
We are looking for curious and motivated software engineers to help build the systems that make autonomous trucking possible.
Depending on your interests, experience, and business needs, you may work on one or more areas, including:
  • Full-stack and operational applications
  • Distributed systems and backend services
  • Developer and core infrastructure platforms
  • Data processing and workflow orchestration
  • Machine learning infrastructure
  • Simulation and evaluation applications
  • Build, release, and deployment tooling

You do not need prior experience in every area. We are looking for engineers with strong fundamentals, an eagerness to learn, and the ability to solve practical problems collaboratively. You will work alongside experienced engineers and develop expertise through real projects that directly support our autonomous vehicles and operations.
Key Responsibilities
  • Design, implement, test, and maintain software features under the guidance of experienced engineers.
  • Build user-facing applications, backend services, APIs, data pipelines, or internal engineering tools.
  • Develop responsive web interfaces using technologies such as React and TypeScript.
  • Build backend services and workflow automation, primarily using Python and, where appropriate, Go.
  • Work with databases, event-driven systems, and real-time data to connect applications, infrastructure, and autonomous vehicle operations.
  • Contribute to platforms supporting areas such as fleet operations, simulation, machine learning, data processing, CI/CD, and software deployment.
  • Debug software issues and help improve system reliability, performance, usability, and observability.
  • Write clean, maintainable, well-tested, and well-documented code.
  • Participate in code reviews, technical discussions, testing, deployment, and production support.
  • Collaborate with engineers, product managers, autonomy teams, and operations teams to translate real-world needs into dependable software.
  • Learn new technologies and engineering practices as your responsibilities grow.
Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
  • 0-3 years of professional software engineering experience. New graduates with strong academic, internship, open-source, or personal project experience are encouraged to apply.
  • Programming proficiency in at least one general-purpose language, preferably Python, Go, JavaScript/TypeScript, Java, or C++.
  • Solid understanding of software engineering fundamentals, including data structures, algorithms, debugging, testing, and source control.
  • Ability to break down problems, learn unfamiliar systems, and deliver well-scoped work.
  • Strong written and verbal communication skills.
  • Collaborative mindset, attention to detail, and willingness to receive and apply feedback.
Preferred Qualifications
Experience in one or more of the following areas is helpful but not required:
  • Full-stack web development using React, TypeScript, and modern frontend tooling.
  • Backend service or API development using Python or Go.
  • SQL or NoSQL databases.
  • Distributed systems, asynchronous processing, or event-driven architectures.
  • Data processing, batch workflows, or workflow orchestration systems.
  • Machine learning pipelines, model evaluation, experiment tracking, annotation, or dataset management.
  • Simulation, visualization, geospatial applications, or real-time operational interfaces.
  • Docker, Kubernetes, or cloud platforms such as AWS.
  • CI/CD systems, build tools, package management, or developer productivity tooling.
  • Streaming and messaging technologies such as NATS, Kafka, MQTT, or WebSockets.
  • Observability tools such as metrics, logging, tracing, dashboards, or alerting.
  • Autonomous vehicles, robotics, transportation, logistics, or other systems that interact with the physical world.
What We Value
  • Strong engineering fundamentals over familiarity with a particular technology stack.
  • Demonstrated ability to build, debug, or improve working software.
  • Curiosity about how systems work across application, infrastructure, and operational boundaries.
  • Ownership of your work while knowing when to ask for help.
  • Thoughtful consideration of reliability, usability, maintainability, and real-world impact.
  • Interest in growing into a versatile engineer who can contribute across multiple technical domains.

At Bot Auto, engineers are not limited to isolated tasks. You will contribute to production systems, learn from experienced teammates, and have opportunities to explore different engineering areas as the company and your career grow.

Apply