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Internship Medical Imaging Machine Learning Jobs in Arizona

Intel

Sr. Machine Learning Engineer

Phoenix, AZ · On-site

$103K - $142K/yr

... internship experiences and or schoolwork/classes/research. Benefits at Intel Our total rewards ... Candidates should never be required to pay recruitment fees, medical examination fees, or any other ...

Banner Health

Clinical Faculty Abdominal Imaging

Tucson, AZ · On-site

$33 - $42.50/hr

Banner - University Medicine Tucson and the University of Arizona - Department of Medical Imaging ... learning environment for the delivery of innovative education. Job Responsibilities: * Contribute ...

Axon

Senior Machine Learning Scientist

Scottsdale, AZ · On-site

$92K - $125K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI ... Medical, Dental, Vision plans * Fitness Programs * Emotional & Mental Wellness support * Learning ...

Axon

Senior Machine Learning Scientist

Scottsdale, AZ · On-site

$92K - $125K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI ... Medical, Dental, Vision plans * Fitness Programs * Emotional & Mental Wellness support * Learning ...

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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 Arizona?

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Internship Medical Imaging Machine Learning jobs near you

Sr. Machine Learning Engineer

Intel

Phoenix, AZ • On-site

$103K - $142K/yr

Full-time

Medical, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

Intel rating

8.7

Company rating: 8.7 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

18th of 159 rated electronics manufacturers

Job description

Job Details:Job Description: 
Job Description
Our Mission

At Intel, our journey is to transform AI into something safer, more trustworthy, and respectful of human privacy by design. We believe transformative AI should have a positive impact on people-powerful in capability, yet honest about its limits and protective of the data and resources it touches.

To get there, we build agentic AI that combines the best of local and cloud intelligence - private, affordable, and sustainable by design. Small, efficient models run directly on the user's machine (AI PC, edge, on-prem, and beyond), keeping data private and token costs low, while powerful cloud models handle the hardest work: planning, reasoning, and complex problem-solving. Today, neither approach can deliver this alone. Together, they give people real capability without compromise-data stays private, spend stays predictable, and energy use stays in check.

We're building intelligence that scales without sacrificing trust, cost, or the planet-because the future of AI should belong to the people it serves

Role Summary

We are seeking a **Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research and model fine tuning. This role sits at the intersection of research and engineering: the ideal candidate designs and implements algorithms for agent harness and post-training pipelines, develops RL environments and reward models, and conducts training runs to improve model capabilities for agentic applications.

What you'll do

Work in a dynamic team to:

  • Build evaluation benchmarks and metrics

  • Build and iterate on agent harness, including context engineering, agent memory, tools, skills.

  • Build, maintain, and iterate on the post-training pipeline: Develop robust, reproducible training workflows from data ingestion and preprocessing through model checkpointing and deployment

  • Design RL environments and reward functions - Develop environments, reward signals, and verifiable reward frameworks for training models on reasoning-intensive tasks.

  • Debug and optimize training runs - Profile training jobs, resolve bottlenecks, improve GPU utilization, and address numerical instability at multi-GPU scale

What you'll learn / grow into

Curiosity is required. You will develop:

  • How post-training techniques actually move model performance

  • How to make small models punch above their weight as agent backends

  • How model choices interact with runtime constraints on edge hardware

IMPORTANT:

Please be informed that Intel is proactively trying

to find candidates for this position which is frequently available

at Intel.

Please note that the position may not be available

at this time. If you would be interested in this position should it

become available, we would encourage you to apply, and our

hiring team will be glad to contact you when/if relevant.

Qualifications:
Qualifications

Minimum qualifications are required to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
You must possess the minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.

Required Qualifications

  • BS in CS, EE, Math or related STEM field

  • 8+ years software development background

  • 4+ years of hands-on experience in machine learning engineering, data science or ML research.

  • Experiences designing and building evaluation frameworks and benchmarks that accurately measure model capability improvements and alignment quality

  • Proficient in Python

  • Proficient in LLM architectures, optimization and model training dynamics.

Preferred Qualifications

  • Masters or PhD degrees are preferred.

  • Hands-on experience implementing and scaling the full **post-training pipeline** for language models including supervised fine tuning and reinforcement learning.

  • Ability to own and drive a research agenda independently, generating hypotheses and prioritizing experiments without step-by-step supervision.

  • Ambiguity tolerance: Comfortable making progress in fast-moving environments where problem definitions evolve and priorities shift.

  • Debug-first mindset: Willingness and skill to dive deeply into large, complex ML codebases to isolate and fix subtle issues.

  • Research-engineering balance: Ability to produce production-quality implementations of novel research ideas, balancing rigor with speed.

  • Collaborative work style: Comfort with cross-functional collaboration.

  • Clear technical communication: Ability to explain research results, architectural decisions, and trade-offs to both technical and non-technical stakeholders.

  • Ability to learn new technologies fast and adapt to changes with open-mindedness.

Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research.

Benefits at Intel

Our total rewards package goes above and beyond just a paycheck. Whether you're looking to build your career, improve your health, or protect your wealth, we offer generous benefits to help you achieve your goals. Go to Intel Benefits | Intel Careers for details of benefits available to you. Intel reserves the right to modify, change or discontinue benefit plans at any time in its sole discretion.

#LDI

Job Type:Shift:Shift 1 (United States of America)Primary Location: US, California, Santa ClaraAdditional Locations:US, Arizona, Phoenix, US, California, Folsom, US, Oregon, HillsboroPosting Statement:All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.Position of TrustN/ABenefits

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.

Annual Salary Range for jobs which could be performed in the US: $195,200.00-361,200.00 USDThe range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. 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 compensation range for your preferred location during the hiring process.

Work Model for this Role

This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.

*

ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.

What Intel employees say

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Benefits

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Workplace

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About Intel

Sourced by ZipRecruiter

Intel strives to make every facet of semiconductor manufacturing state-of-the-art -- from semiconductor process development and manufacturing, through yield improvement to packaging, final test and optimization, and world class Supply Chain and facilities support. Employees in the Technology and Manufacturing Group are part of a worldwide network of design, development, manufacturing, and assembly/test facilities, all focused on utilizing the power of Moore's Law to bring smart, connected devices to every person on Earth

Industry

Manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1968

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