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Undergraduate Machine Learning Internship Jobs (NOW HIRING)

Hive

Machine Learning Engineer

San Francisco, CA

$120K - $180K/yr

You have an undergraduate or graduate degree in computer science or similar technical field, with significant coursework in mathematics or statistics * You have 1-2 years industry machine learning ...

Hive

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

You have an undergraduate or graduate degree in computer science or similar technical field, with significant coursework in mathematics or statistics * You have 1-2 years industry machine learning ...

Hive

Machine Learning Engineer

Seattle, WA

$120K - $180K/yr

You have an undergraduate or graduate degree in computer science or similar technical field, with significant coursework in mathematics or statistics * You have 1-2 years industry machine learning ...

Hive

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

You have an undergraduate or graduate degree in computer science or similar technical field, with significant coursework in mathematics or statistics * You have 1-2 years industry machine learning ...

Photon

Machine Learning Engineer - NJ

Dallas, TX · On-site

Machine Learning Engineer We are seeking a Machine Learning Engineer to design and develop robust ... Undergraduate or Graduate degree in Computer Science, Mathematics, Physics, or related fields. A ...

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Undergraduate Machine Learning Internship information

See salary details

$25.5K

$42.6K

$88K

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

As of Jun 9, 2026, the average yearly pay for undergraduate machine learning internship 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 is an Undergraduate Machine Learning Internship job?

An Undergraduate Machine Learning Internship is a temporary position designed for students pursuing a bachelor's degree who want hands-on experience in machine learning. Interns typically work on real-world projects involving data preprocessing, model development, and performance evaluation under the guidance of experienced engineers or researchers. They may also assist with research, implement algorithms, and optimize models for deployment. The role helps students gain practical skills in coding, data analysis, and machine learning frameworks while preparing them for future careers in AI and data science.

What are the key skills and qualifications needed to thrive in the Undergraduate Machine Learning Internship position, and why are they important?

To thrive as an Undergraduate Machine Learning Intern, you typically need a strong foundation in mathematics, statistics, and programming (Python or R), often supported by ongoing studies in computer science, data science, or a related field. Experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch, and familiarity with data analysis tools are commonly valued. Curiosity, strong problem-solving abilities, and the willingness to work collaboratively in a team make candidates stand out. These skills and qualities are crucial for learning quickly, making meaningful contributions to real projects, and growing in a fast-paced, technical environment.

What types of projects or tasks can I expect to work on during an Undergraduate Machine Learning Internship?

As an Undergraduate Machine Learning Intern, you can expect to assist with tasks such as data preprocessing, model development and evaluation, and implementing machine learning algorithms under the guidance of experienced team members. You may also be involved in cleaning and exploring data sets, creating visualizations, and helping automate parts of the data pipeline. Collaborating with data scientists and engineers, you’ll likely participate in team meetings, code reviews, and brainstorming sessions to address real-world business or research challenges. These hands-on experiences are designed to help you build practical skills and gain exposure to the workflow of professional machine learning projects.

More about Undergraduate Machine Learning Internship jobs
What cities are hiring for Undergraduate Machine Learning Internship jobs? Cities with the most Undergraduate Machine Learning Internship job openings:
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Undergraduate Machine Learning Internship jobs near you
Infographic showing various Undergraduate Machine Learning Internship job openings in the United States as of June 2026, with employment types broken down into 13% Full Time, and 87% Part Time. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Machine Learning Engineer

Machine Learning Engineer

Hive

San Francisco, CA

$120K - $180K/yr

Full-time

Posted 6 days ago

Job description

About Hive

Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive's solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more.

Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI!

Machine Learning Role

In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the forefront of deep learning technology, prototyping state-of-the-art neural net models and launching these models into production. We value hard workers who have no qualms working with terabyte-scale datasets, who are interested in learning new technologies at all levels of the machine learning stack, and who move fast and take ownership of their projects. Our ideal candidate has experience creating a working machine learning-powered project from the ground up, contributes innovative ideas and ingenious implementations to the team, and is capable of planning out scalable, maintainable data pipelines.
Responsibilities
  • Everything involved in applying a ML model to a production use case, including, designing and coding up the neural network, gathering and refining data, training and tuning the model, deploying it at scale with high throughput and uptime, and analyzing the results in the wild in order to continuously update and improve accuracy and speed
  • Interface closely with the Backend and DevOps teams as well as with our internal data labeling services
  • Utilize OWASP top 10 techniques to secure code from vulnerabilities
  • Maintain awareness of industry best practices for data maintenance handling as it relates to your role
  • Adhere to policies, guidelines and procedures pertaining to the protection of information assets
  • Report actual or suspected security and/or policy violations/breaches to an appropriate authority
Requirements
  • You have an undergraduate or graduate degree in computer science or similar technical field, with significant coursework in mathematics or statistics
  • You have 1-2 years industry machine learning experience
  • You have successfully trained and deployed a deep learning machine model (image, NLP, video, or audio) into production, with measurably improved performance over baseline, either in industry or as a personal project
  • You have strong experience with a high-level machine learning frameworks such as Tensorflow, Caffe, or Torch, and familiarity with the others
  • You know the ins and outs of Python, especially as it applies to the above ML frameworks
  • You are capable of quickly coding and prototyping data pipelines involving any combination of Python, Node, bash, and linux command-line tools, especially when applied to large datasets consisting of millions of files
  • You have a working knowledge of the following technologies, or are not afraid of picking it up on the fly: C++, Scala/Spark, SQL, Cassandra, Docker
  • You are up-to-date on the latest deep neural net research and architectures, both in understanding the theory and motivations behind the techniques, as well as how to implement them in the ML framework of your choice
  • You have great communication skills and ability to work with others
  • You are a strong team player, with a do-whatever-it-takes attitude
Who We Are

We are a group of ambitious individuals who are passionate about creating a revolutionary AI company. At Hive, you will have a steep learning curve and an opportunity to contribute to one of the fastest growing AI start-ups in San Francisco. The work you do here will have a noticeable and direct impact on the development of the company.

Thank you for your interest in Hive and we hope to meet you soon!

The current expected base salary for this position ranges from $120,000 - $180,000. Actual compensation may vary depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the total compensation package that is provided to compensate and recognize employees for their work; stock options may be offered in addition to the range provided here.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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