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Medical Machine Learning Internship Jobs (NOW HIRING)

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Machine Learning Intern

Mountain View, CA · Hybrid

$40/hr

This internship will pay $40 per hour, with an expected 40 hours per week for the 12-week program ... of machine learning and deep learning algorithms. Familiarity with training or fine-tuning large ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

Avride

Machine Learning Engineer Internship

Austin, TX · On-site

About the Internship At Avride, ML Engineer Interns operate at the intersection of cutting-edge ... Machine Learning / Math Foundation: Strong understanding of deep learning, reinforcement learning ...

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

As of May 31, 2026, the average yearly pay for medical 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 are the key skills and qualifications needed to thrive as a Medical Machine Learning Intern, and why are they important?

To thrive as a Medical Machine Learning Intern, you need a solid background in statistics, programming (Python or R), and foundational knowledge of machine learning algorithms, typically supported by coursework or a relevant degree in computer science, engineering, or a related field. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and experience working with medical datasets or healthcare IT systems are highly valued. Strong analytical thinking, attention to detail, and effective communication skills will help you collaborate with interdisciplinary teams and present findings clearly. These skills are crucial for developing accurate, impactful models that address real-world healthcare challenges and ensure patient safety.

What kinds of projects and responsibilities can I expect during a Medical Machine Learning Internship?

As a Medical Machine Learning Intern, you'll typically work on real-world datasets to develop, test, and refine machine learning models aimed at improving healthcare outcomes. Your daily tasks may include data preprocessing, feature engineering, model selection, and performance evaluation under the guidance of experienced data scientists or clinicians. Collaboration is key, as you'll often work with multidisciplinary teams, including software engineers, clinicians, and researchers. This hands-on experience allows you to gain practical skills and contribute to impactful projects that can enhance patient care or medical research.

What is a Medical Machine Learning Internship?

A Medical Machine Learning Internship is a temporary position where students or recent graduates work on projects that apply machine learning techniques to healthcare and medical datasets. Interns typically collaborate with data scientists, clinicians, and researchers to develop algorithms that can assist in diagnosing diseases, predicting patient outcomes, or improving healthcare processes. This role provides hands-on experience with real-world medical data, exposure to regulatory considerations, and the opportunity to contribute to impactful healthcare innovations. Such internships help interns build technical and domain-specific skills, preparing them for future careers in medical data science.
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Medical Machine Learning Internship jobs near you
Machine Learning Intern

Machine Learning Intern

EarnIn

Mountain View, CA • Hybrid

$40/hr

Other

Posted 22 days ago

Job description

POSITION SUMMARY

As a Fintech company where Machine Learning (ML) is one of the key drivers of growth, our operations highly rely on machine learning models, from business decisions to customer experiences. Therefore, building and deploying state-of-the-art machine learning systems to drive impact via our data capabilities is key. To guarantee the success of machine learning systems, we need to provide a detailed formulation, extensive experimentation, and to transform ML models into high-performance production-level code, including not only implementing sophisticated machine learning algorithms but also robustness monitoring and system logging/alarming. 

 We seek talented and motivated students and recent graduates with a strong background in machine learning, deep learning, language models and generative AI, programming, and data analysis to join our 12-week Machine Learning Internship Program. You will work on real-world projects, collaborate with experienced professionals, gain valuable experience in the fintech industry, and realize business and social impact. This role requires hybrid work from our Mountain View office, with 2 days a week in person. This internship will pay $40 per hour, with an expected 40 hours per week for the 12-week program. We are unable to provide visa sponsorship or immigration support for this position.  

WHAT YOU'LL DO 

  • Train and fine-tune large-scale Foundation Models to support various fintech product use cases
  • Work with a large dataset, including structured and unstructured data
  • Help in ensuring improvements in our current ML systems via model, data, or experimentation upgrades
  • Gain hands-on experience with a wide array of technologies, including PyTorch, AWS, Kafka, Databricks, etc

WHAT WE'RE LOOKING FOR

  • Actively pursuing a Master's or PhD in Computer Science, Information Technology, or a related field
  • Located in Mountain View, or have the ability to relocate there, for the duration of the internship 
  • Strong understanding of statistical models, familiarity, and in-depth understanding of machine learning and deep learning algorithms. Familiarity with training or fine-tuning large-scale models, Sequence Transformer models 
  • Interest in multimodal or multitask learning across structured, sequential, and behavioral data
  • Familiarity with AI tools, harness engineering, agentic workflow, etc.
  • Hands-on programming experience in Python and ML frameworks such as PyTorch
  • Equipped with good verbal and written communication skills
  • A background demonstrating strong problem-solving skills
  • Committed to taking ownership of projects, conducting thorough investigations, and driving initiatives to conclusion

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