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Internship Medical Imaging Machine Learning Jobs in Houston, TX

Crowe LLP

Machine Learning Intern

Houston, TX

$27 - $42/hr

DS interns will have a designated data scientist mentor and will spend the majority of their time working on a data science project overseen by that mentor. The expectation is that at the end of the ...

Crowe LLP

Machine Learning Intern

The Woodlands, TX

$27 - $42/hr

DS interns will have a designated data scientist mentor and will spend the majority of their time working on a data science project overseen by that mentor. The expectation is that at the end of the ...

Crowe LLP

Machine Learning Intern

The Woodlands, TX · On-site

$27 - $42/hr

DS interns will have a designated data scientist mentor and will spend the majority of their time working on a data science project overseen by that mentor. The expectation is that at the end of the ...

Crowe LLP

Machine Learning Intern

Houston, TX · On-site

$27 - $42/hr

DS interns will have a designated data scientist mentor and will spend the majority of their time working on a data science project overseen by that mentor. The expectation is that at the end of the ...

NobleAI

Lead Machine Learning Engineer

Houston, TX · On-site +1

$97K - $128K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI ... Top-tier health benefits coverage, including medical, dental, vision, disability and life insurance

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Internship Medical Imaging Machine Learning information

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$24.4K

$40.7K

$84K

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

As of Aug 30, 2026, the average yearly pay for internship medical imaging machine learning in Houston, TX is $40,666.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,000.00 and $43,900.00 per year, depending on experience, location, and employer.

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 Houston, TX?

The most popular types of Medical Imaging Machine Learning jobs in Houston, TX are:

What are popular job titles related to Internship Medical Imaging Machine Learning jobs in Houston, TX?

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

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

The top searched job categories for Internship Medical Imaging Machine Learning jobs in Houston, TX are:

What cities near Houston, TX are hiring for Internship Medical Imaging Machine Learning jobs?

Cities near Houston, TX 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 Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 13% Part Time, 2% Temporary, and 5% Contract. Highlights an 87% Physical, 1% Hybrid, and 12% Remote job distribution, with an average salary of $40,666 per year, or $19.6 per hour.

Senior Machine Learning Engineer - Medical Imaging

Houston, TX • On-site

MD Anderson Center
Health Care and Social Assistance • 10K+ employees

8.5

Company rating: 8.5 out of 10

Based on 172 frontline employees who took The Breakroom Quiz

14th of 895 rated healthcare providers

People enjoy working here

Good employer

Recommended by students

Learn more about MD Anderson Centerexternal

$99K - $137K/yr

Full-time

Medical, Dental, Retirement, PTO

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

Job description

As a Senior Machine Learning Engineer specializing in medical imaging within the Data Impact & Governance department, you will help shape the future of clinical AI by building, deploying, and operating imaging models that directly impact patient care. This role offers the unique opportunity to work at the cutting edge of applied medical imaging ML within a world-renowned cancer center-where your solutions influence diagnosis, treatment, safety, and operational excellence.
What's in it for you?
  • Exceptional Benefits: MD Anderson provides paid medical benefits, generous PTO, and strong retirement plans, supporting your health, well-being, and long-term financial security.
  • High-Impact Work: Your models will be used in real clinical workflows-helping clinicians detect disease, streamline operations, and support better outcomes for patients.
  • Advanced Technical Environment: Work with large-scale imaging datasets, enterprise GPU infrastructure, distributed compute, and cutting-edge ML technologies-all within a governed clinical environment.
  • Career Growth & Visibility: Collaborate closely with clinicians, data scientists, ML leadership, radiologists, and operational teams. Your work will influence institutional AI strategy and governance.
  • Innovation with Responsibility: Help advance safe, ethical, and trustworthy AI practices in one of the world's leading cancer centers.
  • Collaborative Culture: Be part of a mission-driven organization that values innovation, learning, and teamwork.

Summary
The Senior Machine Learning Engineer - Medical Imaging owns the full lifecycle of clinical computer vision models deployed across the enterprise. This includes defining clinical ML problems, designing and training models, conducting rigorous validation, deploying models into clinical environments, and ensuring ongoing performance and reliability in real-world workflows.
The role is intended for engineers experienced in deploying and operating medical imaging ML models in production-especially within regulated, clinical, or safety-sensitive settings. You will collaborate with multidisciplinary teams, investigate model performance issues such as distribution shift or protocol variability, and ensure responsible AI adoption through strong documentation, traceability, and governance alignment.
Major Work Activities
Core Responsibilities
  • Own the full lifecycle of medical imaging ML models-from problem definition and model development to deployment, monitoring, maintenance, and retirement.
  • Participate as a technical owner in formal governance, release, and incident review processes, with clear escalation paths and responsibilities.
  • Translate clinical imaging use cases into deployable AI solutions with defined evaluation metrics, operating thresholds, and reproducible implementation strategies.
  • Design and execute post-deployment monitoring, including detection and mitigation of model degradation due to distribution shift, scanner changes, or labeling variability.
  • Collaborate with ML platform, data science, IT, and clinical operations teams to deploy and operate models in secure enterprise environments.
  • Maintain responsible AI practices, ensuring traceability of data, models, experiments, and documentation of limitations and failure modes.
  • Contribute to fallback, rollback, and model decommissioning strategies to support patient safety and operational continuity.
  • Engage clinical, technical, and operational partners to support safe adoption and communicate model risks, behaviors, and performance.
  • Mentor junior team members and contribute to best practices, review standards, and reproducible ML workflows.

Competencies
Technical Expertise
  • Experience developing, deploying, and operating medical imaging ML models in regulated clinical environments.
  • Ability to build imaging data pipelines involving DICOM workflows, dataset versioning, and distributed training.
  • Deep proficiency in Python and PyTorch for model training and inference under GPU and memory constraints.
  • Experience orchestrating ML workflows using Airflow, Prefect, or similar DAG-based systems.
  • Skilled in deploying containerized ML workloads on enterprise cloud platforms such as Azure using Kubernetes.
  • Understanding of audit-ready model tracking, lineage, and controlled promotion workflows.

Analytical Expertise
  • Ability to scope medical imaging ML projects end to end, considering clinical and regulatory constraints.
  • Experience designing validation strategies aligned with governance, regulatory expectations, and change control processes.
  • Knowledge of healthcare data privacy requirements as they relate to medical imaging and clinical metadata.
  • Ability to evaluate model performance quantitatively in the context of clinical workflows and operational realities.
  • Experience engaging clinicians, patient safety, and business stakeholders to communicate model performance, impacts, and risk considerations.
  • Ability to assess model generalizability and failure modes across scanners, sites, and populations.

Oral & Written Communication
  • Collaborate effectively with data scientists, ML engineers, software teams, clinicians, and operational leaders to integrate imaging models into real workflows.
  • Produce clear, comprehensive technical documentation including design specs, validation reports, and runbooks.
  • Communicate project risks, timelines, and outcomes to leadership and governance bodies.
  • Contribute to internal technical standards, best practices, and shared ML development frameworks.
  • Present technical and non-technical updates clearly across multiple stakeholder groups.

Education Required: Bachelor's degree in Computer Science, Software Engineering, Data Science, Physics, Math & Statistics, or another related engineering discipline.
Preferred Education: Master's Degree or PHD with a concertation in Science, Engineering, or related field.
Experience Required: Five years of experience in machine learning engineering, data science, data engineering, and/or software engineering. With Master's degree, three years' experience required. With PhD, one year of experience required.
Preferred Experience:
  • Experience operating medical imaging ML systems across multiple sites, scanners, or protocols, rather than a single controlled environment.
  • Experience handling post-deployment failures, including performance degradation, clinical incidents, model updates, or corrective actions.
  • Experience raising the technical bar for team members, such as establishing reproducibility practices, review standards, or shared patterns.
  • Experience technically evaluating third-party medical imaging AI within clinical workflows.
    The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition.
    This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.
    It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html

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