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Internship Medical Imaging Machine Learning Jobs in California

Voxelcloud

Machine Learning Engineer

Los Angeles, CA · On-site

... to medical imaging applications, including disease detection/quantification in medical scans ... We are currently hiring both full-time and interns to join our R&D team. Responsibilities:

Intuitive

Sr. Machine Learning Engineer

Sunnyvale, CA · On-site

$143K - $189K/yr

Drive the full cycle of medical imaging analysis software development, developing algorithms from R&D concepts into robust, commercial medical device products. * Design, prototype, and implement ...

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Internship Medical Imaging Machine Learning information

What is an internship in medical imaging machine learning?

An Internship in Medical Imaging Machine Learning is a temporary position, typically held by students or recent graduates, where individuals gain practical experience applying machine learning techniques to medical imaging data. Interns work alongside professionals to develop, train, and evaluate algorithms that help interpret medical images such as X-rays, MRIs, or CT scans. These roles often involve data preprocessing, model development, and performance analysis, providing valuable hands-on experience in both healthcare and artificial intelligence. This internship is ideal for those interested in combining expertise in computer science, machine learning, and medical diagnostics.

What types of projects can I expect to work on during an internship in medical imaging machine learning?

As an intern in medical imaging machine learning, you'll typically contribute to projects involving the development and validation of algorithms for tasks such as image segmentation, classification, or anomaly detection using clinical imaging data. Daily responsibilities often include data preprocessing, model training and evaluation, and collaborating with research scientists and clinicians to interpret results. You'll also have opportunities to participate in team meetings, present findings, and receive mentorship, which can help you build both technical and domain-specific skills for future roles in healthcare AI.

What are the key skills and qualifications needed to thrive as an intern in medical imaging machine learning?

To thrive in a Medical Imaging Machine Learning internship, you need a solid background in computer science, mathematics, and biomedical engineering, typically supported by coursework or experience in machine learning and image processing. Familiarity with Python, TensorFlow or PyTorch, and medical imaging tools such as DICOM viewers is commonly required. Strong analytical thinking, problem-solving abilities, and effective teamwork set candidates apart in this field. These skills and qualities enable interns to contribute meaningfully to research and development projects, ensuring accurate analysis and innovation in medical imaging solutions.

What are the most commonly searched types of Medical Imaging Machine Learning jobs in California?

The most popular types of Medical Imaging Machine Learning jobs in California are:

What are popular job titles related to Internship Medical Imaging Machine Learning jobs in California?

For Internship Medical Imaging Machine Learning jobs in California, the most frequently searched job titles are:

What job categories do people searching Internship Medical Imaging Machine Learning jobs in California look for?

The top searched job categories for Internship Medical Imaging Machine Learning jobs in California are:

What cities in California are hiring for Internship Medical Imaging Machine Learning jobs?

Cities in California with the most Internship Medical Imaging Machine Learning job openings:

Internship Medical Imaging Machine Learning jobs near you
Infographic showing various Internship Medical Imaging Machine Learning job openings in California as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 18% Part Time, and 7% Contract. Highlights an 87% Physical, 1% Hybrid, and 12% Remote job distribution.

Imaging Machine Learning Engineer

Mountain View, CA • On-site

Google Inc.
Software Development • 10K+ employees

8.8

Company rating: 8.8 out of 10

Based on 103 frontline employees who took The Breakroom Quiz

48th of 246 rated software companies

Free food

Great coworkers

People enjoy working here

Learn more about Google Inc.external

$136 - $186/hr

Other

Posted 16 days ago

Job description

corporate_fare Google place Mountain View, CA, USA

Mid

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

  • Bachelor’s degree in Electrical Engineering, Computer Science, Imaging Science, Physics, or a related field, or equivalent practical experience.
  • 2 years of experience in Image Quality, Computer Vision, or a related technical field.
  • 2 years of experience in Python and C++ for algorithm development and implementation.
Preferred qualifications:
  • Master’s degree, or PhD in a related field.
  • 3 years of professional experience in a related field.
  • Industry experience in SoC/ISP constraints, 3A tuning, or the application of Deep Learning to real-time imaging pipelines.
  • A proven track record of delivering high-quality, commercial, market-facing consumer cameras.
  • A strong track record of self-driven learning and the capability to rapidly master new technologies and domains.
  • Excellent written and verbal communication skills, with a demonstrated ability to translate technical concepts into clear, actionable insights for cross-functional partners.
About the job

The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $132000 - $189000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

  • Optimize image quality across the hardware and software stack, ensuring hardware capabilities are leveraged through software tuning.
  • Fine-tune 3A algorithms to ensure performance across lighting and environmental conditions.
  • Build software tools, utilizing machine learning (ML) automation to streamline image quality (IQ) tuning, testing, benchmarking, and calibration workflows.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.

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