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Internship Machine Learning Engineer Jobs (NOW HIRING)

About the role: We're looking for an early career Machine Learning Engineer to join our team. In this role you will build and deploy state of the art machine learning models to solve complex ...

Job Title Machine Learning Engineer Location Remote Rate $48/hr on W2 Must Haves: Neaural networks NLP Python AZURE Pytorch or tensorflow Machine Learning Engineer / AI Engineer Role Role Overview ...

About the role: We're looking for an early career Machine Learning Engineer to join our team. In this role you will build and deploy state of the art machine learning models to solve complex ...

Lead Machine Learning Engineer

Mclean, VA

$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 ...

Machine Learning Engineer We're looking for a talented and motivated Machine Learning Engineer to join our team and help develop cutting-edge AI solutions. In this role, you'll have the opportunity ...

We are looking for a Machine Learning Engineer to design, build, and deploy machine learning systems that improve the calibration, control, and operation of quantum processors. In this role, you will ...

Lead Machine Learning Engineer

Plano, TX

$98K - $129K/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 ...

Showing results 41-60

Internship Machine Learning Engineer information

See salary details

$25.5K

$42.6K

$88K

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

As of Sep 14, 2026, the average yearly pay for internship machine learning engineer in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What does an internship machine learning engineer do?

An Internship Machine Learning Engineer works alongside experienced engineers to help develop, test, and deploy machine learning models. Their responsibilities may include cleaning and preparing data, writing code for model training, evaluating model performance, and contributing to research tasks. Interns often learn to use popular frameworks such as TensorFlow or PyTorch and gain hands-on experience with real-world datasets. This role is designed to help students or recent graduates apply their academic knowledge to practical problems while developing industry-relevant skills.

What types of projects and responsibilities can I expect as an internship machine learning engineer?

As an Internship Machine Learning Engineer, you will typically support the development, testing, and deployment of machine learning models under the guidance of senior engineers. Your responsibilities may include data preprocessing, exploratory data analysis, implementing algorithms, and evaluating model performance. You'll often collaborate closely with data scientists, software engineers, and product managers, gaining exposure to real-world workflows and tools. This hands-on experience is invaluable for building technical skills and understanding how machine learning solutions are integrated into larger products.

What are the key skills and qualifications needed to thrive as an internship machine learning engineer, and why are they important?

To excel as an Internship Machine Learning Engineer, you typically need a solid background in mathematics, programming (especially Python), and foundational machine learning concepts, often supported by coursework or relevant project experience. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is common, along with proficiency in data processing libraries. Curiosity, strong problem-solving abilities, and effective teamwork and communication skills help set candidates apart. These competencies ensure you can contribute meaningfully to projects, adapt to new challenges, and collaborate productively in a rapidly evolving technical environment.

What is the difference between Internship Machine Learning Engineer vs Data Scientist Intern?

AspectInternship Machine Learning EngineerData Scientist Intern
Required CredentialsBasic programming, introductory ML knowledgeStatistics, data analysis, programming
Work EnvironmentDeveloping ML models, coding, testingData analysis, visualization, reporting
Employer & Industry UsageTech companies, startups, AI firmsTech, finance, healthcare, consulting

Internship Machine Learning Engineers focus on developing and testing machine learning models, often requiring programming and basic ML knowledge. Data Scientist Interns analyze data, create visualizations, and generate insights. Both roles are common in tech and data-driven industries, but ML Engineer internships emphasize model deployment, while Data Science internships focus on data analysis and reporting.

What cities are hiring for Internship Machine Learning Engineer jobs?

Cities with the most Internship Machine Learning Engineer job openings:

What are the most commonly searched types of Machine Learning Engineer jobs?

The most popular types of Machine Learning Engineer jobs are:

What states have the most Internship Machine Learning Engineer jobs?

States with the most job openings for Internship Machine Learning Engineer jobs include:

What are popular job titles related to Internship Machine Learning Engineer jobs?

For Internship Machine Learning Engineer jobs, the most frequently searched job titles are:

Infographic showing various Internship Machine Learning Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning Engineer

Mountain View, CA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 18 hours ago


Tapestry Inc. rating

8.2

Company rating: 8.2 out of 10

Based on 36 frontline employees who took The Breakroom Quiz


Job description

About Tapestry

Tapestry is a group within Google working to build the AI-powered electric grid. We are tackling one of the world's most important infrastructure challenges: helping the energy system become more visible, understandable, reliable, affordable, abundant, and clean.

Originally born at X, Alphabet's moonshot factory, Tapestry brings together experts in energy, AI, software engineering, and products to build tools that help the electricity ecosystem plan smarter, move faster, and operate more efficiently.

This is a global effort. Tapestry supports partners across the U.S., U.K., Chile, New Zealand, Australia, and Brazil as they work toward a cleaner, more resilient energy future.

Joining Tapestry means doing high-impact work with a multidisciplinary team tackling a problem that matters at global scale. Learn more about our team and our mission here.

About the role:

We're looking for an early career Machine Learning Engineer to join our team. In this role you will build and deploy state of the art machine learning models to solve complex challenges that face today's electric grid. You will work closely with other Machine Learning Engineers, Data Scientists and Software Engineers across diverse ML domains spanning multimodal machine learning, information retrieval, natural language processing and agentic AI. 

How you will make 10x impact:

  • Train, and deploy machine learning models in production environments.
  • Work with senior team members to develop enterprise quality ML systems, spanning multiple ML domains 
  • Operationalize ML model training at serving at enterprise scale
  • Stay abreast of the latest advancements in machine learning

What you should have:

  • Master's Degree/Bachelor's Degree in Machine Learning, Computer Science,  Statistics or related field
  • 3+ years of experience in machine learning model development and engineering.
  • Expertise in one or more of the following areas: multimodal machine learning NLP or agentic AI, planning, control and reinforcement learning
  • Strong programming skills in Python and experience with ML frameworks like PyTorch or TensorFlow.
  • Experience with building and deploying ML systems at scale, OR  a proven ability to perform  applied ML research and develop the state of the art in an academic setting

It'd be great if you also had these:

  • PhD in Machine Learning, Computer Science, Statistics, or a related field
  • Experience with cloud platforms such as AWS, GCP, or Azure.
  • A strong portfolio of projects demonstrating ML expertise.

Our values

  • Take charge: We take initiative and own outcomes that move the mission forward.
  • Transform with purpose: We build solutions that solve real problems and create meaningful impact.
  • Be a Tapestry, not a thread: We collaborate across diverse skills and perspectives to achieve more than we can individually.
  • Always fine-tune: We stay curious, seek feedback, and refine our understanding as we learn.
  • Stay grounded: We listen openly, value different perspectives, and stay focused on what matters most.

What we offer

A culture that supports growth, ownership, and meaningful impact, along with:

  • Competitive salary and equity
  • Medical, dental, and vision coverage
  • Generous PTO and flexible hybrid work model
  • 401(k) with employer contribution
  • Professional development
  • The ability to work on important real-world problems within an Alphabet-backed environment

The US base salary range for this full-time position is $166,000 - $244,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.

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