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Nvidia Machine Learning Internship Jobs in Boston, MA

NVIDIA operates as a "learning machine," constantly adapting to new opportunities that only we can pursue and that matter globally. Our worldwide team of talented people aims to push the boundaries ...

NVIDIA operates as a "learning machine," constantly adapting to new opportunities that only we can pursue and that matter globally. Our worldwide team of talented people aims to push the boundaries ...

Senior HPC and Quantum Systems Engineer

Westford, MA · Hybrid

$108K - $148K/yr

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... machine learning. Prototype, document, and evaluate end-to-end workflows that demonstrate the ...

Senior HPC and Quantum Systems Engineer

Westford, MA · Hybrid

$108K - $148K/yr

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... machine learning. * Prototype, document, and evaluate end-to-end workflows that demonstrate the ...

Showing results 41-60

Nvidia Machine Learning Internship information

See Boston, MA salary details

$27.7K

$46.3K

$95.6K

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

As of Sep 9, 2026, the average yearly pay for nvidia machine learning internship in Boston, MA is $46,263.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,300.00 and $50,000.00 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 Boston, MA?

The most popular types of Nvidia Machine Learning jobs in Boston, MA are:

What are popular job titles related to Nvidia Machine Learning Internship jobs in Boston, MA?

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

What job categories do people searching Nvidia Machine Learning Internship jobs in Boston, MA look for?

The top searched job categories for Nvidia Machine Learning Internship jobs in Boston, MA are:

Infographic showing various Nvidia Machine Learning Internship job openings in Boston, MA as of June 2026, with employment types broken down into 21% Internship, 72% Full Time, and 7% Part Time. Highlights an 93% In-person, and 7% Remote job distribution, with an average salary of $46,263 per year, or $22.2 per hour.

Lead Machine Learning Engineer (Manager IC)

Cambridge, MA • On-site

$112K - $147K/yr

Other

Re-posted 5 days ago


Job description

Lead Machine Learning Engineer (Manager IC)

At Capital One, we are changing banking for good by creating responsible and reliable AI‑powered systems. Our investments in technology infrastructure and world‑class talent, along with our deep experience in machine learning, position us at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML bring humanity and simplicity to banking.

What You’ll Do
  • Partner with cross‑functional teams of engineers, data scientists, product managers, and designers to deliver AI‑powered products that change how associates work and provide value to customers.
  • Design, develop, test, deploy, and support AI software components that utilize machine learning models, including model evaluation, experimentation, large language model inference, similarity search, guardrails, governance, observability, and agentic AI.
  • Fine‑tune, develop, and evaluate machine learning and foundation models.
  • Collaborate as part of a cross‑functional Agile team to create and enhance software that utilizes state‑of‑the‑art AI and ML capabilities.
  • Contribute thought leadership and technical vision to the long‑term roadmap of pioneering AI systems at Capital One.
  • Leverage a broad stack of Open Source and SaaS AI technologies.
  • Inform ML infrastructure decisions using a deep understanding of ML modeling techniques and associated issues.
  • Retrain, maintain, and monitor models in production.
  • Construct optimized data pipelines to feed ML models.
  • Ensure all code is well‑managed to reduce vulnerabilities, models are well‑governed from a risk perspective, and ML follows best practices in Responsible and Explainable AI.
Ideal Candidate
  • You love to build systems, take pride in the quality of your work, and share our passion to do the right thing.
  • You are a passionate communicator, comfortable with explaining complex technical concepts to non‑technical partners across the business, sometimes in front of large audiences.
  • You stay abreast of the latest research, intuitively understand scientific publications, and judiciously apply novel techniques in production.
  • You adapt quickly and thrive on bringing clarity to large, undefined problems, asking questions, digging deep to uncover root causes, and articulating findings concisely.
  • You are deeply technical with a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to exploit optimization opportunities others miss.
  • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown.
  • Strategic & Business‑Oriented: Think beyond the technology, deeply understand business needs, and prioritize work that delivers the greatest business value.
  • Highly Collaborative & Transparent: Partner seamlessly across engineering, product, and data science teams, communicate progress, blockers, and decisions clearly, and share knowledge proactively.
  • Technically Mature & Humble: Demonstrate professional maturity by committing to and executing on team decisions.
  • Flexible & Fungible: Roll up your sleeves and contribute wherever the team needs you most, adapting to evolving priorities.
  • A Lifelong Learner: Stay current with the latest AI research and apply novel techniques to production systems with a focus on business impact.
Basic Qualifications
  • Bachelor’s Degree
  • At least 6 years of experience designing and building data‑intensive solutions using distributed computing (internship experience does not apply)
  • At least 4 years of experience programming with Python, Scala, or Java
  • At least 2 years of experience building, scaling, and optimizing ML systems
Preferred Qualifications
  • Master’s or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field
  • 7+ years of experience designing, developing, delivering, and supporting AI services at scale
  • 3+ years of experience building production‑ready data pipelines that feed ML models
  • 3+ years of experience with an industry‑recognized ML framework such as scikit‑learn, PyTorch, Dask, Spark, or TensorFlow
  • 3+ years of experience developing AI and ML algorithms or technologies using Python
  • 2+ years of experience with Retrieval Augmented Generation (RAG)
  • 2+ years of experience with data gathering and preparation for ML models
  • 2+ years of people‑leader experience
  • 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation
  • Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
  • Experience leveraging interactive AI tooling to accelerate productivity, using capabilities beyond basic code completion
  • Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, or Azure
Employment Status

At this time, Capital One will not sponsor a new applicant for employment authorization or offer any immigration‑related support for this position.

Salary and Benefits
  • Cambridge, MA: $197,300 - $225,100
  • McLean, VA: $197,300 - $225,100
  • Richmond, VA: $179,400 - $204,700

Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well‑being.

Equal Opportunity Employment

Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non‑discrimination in compliance with applicable federal, state, and local laws.

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