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Internship Applied Scientist Machine Learning Jobs in Spring, TX

WorkNovas LLC

Senior Data Scientist

Houston, TX · On-site

Senior Data Scientist Houston, TX Description: We are looking for a candidate with the ability to ... machine learning) and has applied those skills in solving real world problems across different ...

Crane Worldwide Logistics

Data Scientist

Houston, TX

... applied math, data science, or a related field * 3-7 years of experience in data science, advanced analytics, or a related role * Demonstrated experience delivering end-to-end machine learning ...

Crane Worldwide Logistics

Data Scientist

Houston, TX · On-site

... applied math, data science, or a related field * 3-7 years of experience in data science, advanced analytics, or a related role * Demonstrated experience delivering end-to-end machine learning ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$116K - $154K/yr

They are seeking an experienced Machine Learning Engineer to join their data science and machine learning team, responsible for delivering machine learning models and applications across various ...

ExxonMobil

Computational Scientist

Spring, TX · On-site

Qualifications : Required : • PhD from a recognized university in Engineering, Applied ... learning, machine learning, physics-informed machine learning, reduced-order modeling, multi ...

NOV, Inc.

Senior Data Scientist

Houston, TX

Architect scalable machine learning and forecasting solutions within cloud platforms such as AWS ... Manage and mentor interns, junior data scientists and analysts * Translate advanced analytics ...

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All JobsApplied Scientist Machine Learning JobsInternship Applied Scientist Machine Learning JobsInternship Applied Scientist Machine Learning Jobs in Spring, TX

Internship Applied Scientist Machine Learning information

See Spring, TX salary details

$22.7K

$37.9K

$78.3K

How much do internship applied scientist machine learning jobs pay per year?

As of Jul 16, 2026, the average yearly pay for internship applied scientist machine learning in Spring, TX is $37,895.00, according to ZipRecruiter salary data. Most workers in this role earn between $28,900.00 and $40,900.00 per year, depending on experience, location, and employer.

What types of projects do Internship Applied Scientists in Machine Learning typically work on, and how do they contribute to the team's goals?

Internship Applied Scientists in Machine Learning often collaborate with multidisciplinary teams to tackle real-world problems using data-driven approaches. Typical projects might include developing and fine-tuning machine learning models, conducting experiments to validate hypotheses, or assisting in the deployment of algorithms into production systems. Interns are expected to contribute fresh perspectives, help with data preprocessing, and perform thorough model evaluations. Through these projects, interns gain hands-on experience while directly supporting the team's research and product development objectives.

What is the difference between Internship Applied Scientist Machine Learning vs Internship Data Scientist?

AspectInternship Applied Scientist Machine LearningInternship Data Scientist
Required CredentialsRelevant degrees in Computer Science, Data Science, or related fields; knowledge of ML frameworksDegrees in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentResearch and development teams, focus on ML model developmentBusiness teams, focus on data analysis and insights
Employer & Industry UsageTech companies, AI-focused organizationsVarious industries including tech, finance, healthcare
Comparison Search IntentUnderstanding roles in ML research and developmentUnderstanding data analysis and business insights roles

Internship Applied Scientist Machine Learning roles focus on developing and applying machine learning models, often in research settings. In contrast, Internship Data Scientist positions emphasize analyzing data to generate insights for business decisions. Both roles require strong analytical skills and relevant educational backgrounds, but they differ in their primary focus and work environment.

What are the key skills and qualifications needed to thrive as an Internship Applied Scientist in Machine Learning, and why are they important?

To thrive as an Internship Applied Scientist in Machine Learning, you need a solid background in mathematics, statistics, and computer science, often supported by coursework or research experience in machine learning and data analysis. Familiarity with tools such as Python, TensorFlow, PyTorch, and experience working with large datasets are highly valued, along with knowledge of version control systems like Git. Strong problem-solving skills, curiosity, and the ability to communicate complex concepts clearly set top candidates apart. These competencies are crucial for effectively designing, implementing, and presenting machine learning solutions that address real-world challenges.

What does an Internship Applied Scientist in Machine Learning do?

An Internship Applied Scientist in Machine Learning works on real-world projects involving the design, development, and evaluation of machine learning models and algorithms. Their responsibilities typically include data analysis, building predictive models, experimenting with new techniques, and collaborating with engineers and researchers to solve complex problems. Interns gain hands-on experience with tools like Python, TensorFlow, or PyTorch, and contribute to advancing the company's AI capabilities. The role requires a strong foundation in mathematics, statistics, and computer science, as well as the ability to communicate findings to both technical and non-technical stakeholders.
What are popular job titles related to Internship Applied Scientist Machine Learning jobs in Spring, TX? For Internship Applied Scientist Machine Learning jobs in Spring, TX, the most frequently searched job titles are:
What job categories do people searching Internship Applied Scientist Machine Learning jobs in Spring, TX look for? The top searched job categories for Internship Applied Scientist Machine Learning jobs in Spring, TX are:
What cities near Spring, TX are hiring for Internship Applied Scientist Machine Learning jobs? Cities near Spring, TX with the most Internship Applied Scientist Machine Learning job openings:
Internship Applied Scientist Machine Learning jobs near you
Infographic showing various Internship Applied Scientist Machine Learning job openings in Spring, TX as of July 2026, with employment types broken down into 75% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $37,895 per year, or $18.2 per hour.
Machine Learning Engineer - Platforms

Machine Learning Engineer - Platforms

MD Anderson

Houston, TX

$123K/yr

Full-time

Medical, Dental, Retirement, PTO

Posted 2 days ago

New

MD Anderson Cancer Center rating

8.4

Company rating: 8.4 out of 10

Based on 169 frontline employees who took The Breakroom Quiz

27th of 886 rated healthcare providers

Job description

As a Machine Learning Engineer - Platforms within the Data Impact & Governance organization, you will shape and scale the enterprise AI/ML platform that powers clinical, research, and operational machine learning across the institution. This is a hands-on engineering role with direct influence on how data science workflows operate institution-wide-enabling safe, efficient, and high-impact AI delivery.
You'll work with modern cloud and container technologies, MLOps frameworks, and enterprise-grade tools while building solutions that improve patient care, strengthen operations, and accelerate scientific discovery.
What's in it for you?
  • Exceptional Benefits: Enjoy paid medical benefits, generous paid time off (PTO), strong retirement plans, and a comprehensive benefits package designed to support your total well-being.
  • High-Impact Work: Develop and maintain the platforms that allow clinicians, researchers, and data scientists to bring AI solutions into real-world healthcare environments.
  • Cutting-Edge Technology: Work with Dataiku, Kubernetes, Azure, container technologies, and MLOps frameworks that support large-scale enterprise ML operations.
  • Career Growth: Collaborate with ML engineers, data scientists, architects, and IT teams, gaining exposure to complex, enterprise-wide AI initiatives and governance.
  • Mission-Driven Culture: Your work will contribute directly to improving patient outcomes and advancing research at a nationally recognized cancer center.

Summary
The Machine Learning Engineer - Platforms supports the development, reliability, and scalability of the enterprise AI/ML platform used across clinical and business operations. The role focuses on MLOps engineering, platform integration, automation, container management, model monitoring, and lifecycle governance. The engineer partners closely with data scientists, ML engineers, and enterprise IT teams to support AI development and deployment, while ensuring compliance, performance, and responsible AI practices.
Major Work Activities
Technical Expertise
  • Support development, administration, and maintenance of the enterprise AI/ML platform (Dataiku, Kubernetes, Azure), ensuring scalability, reliability, and smooth integration with institutional systems.
  • Orchestrate training, deployment, and inference pipelines within Dataiku targeting Azure and on-premises Kubernetes clusters.
  • Develop and maintain MLOps workflows for reproducibility, version control, governance, and model lifecycle management.
  • Manage and optimize containerized environments using Docker and Kubernetes to support data science workloads.
  • Provide platform support for data scientists and ML engineers, troubleshooting environment, pipeline, and dependency issues.
  • Monitor platform performance, cost, security, and compliance, ensuring alignment with enterprise and regulatory standards.

Analytical Skills
  • Build and support scalable pipelines in Dataiku, Kubernetes, and Azure, including feature engineering, model tracking, and validation workflows.
  • Debug, test, and resolve complex platform or pipeline issues using strong analytical and problem-solving skills.
  • Assist with healthcare data integration using standards such as HL7, FHIR, or DICOM when required for model development.

Professionalism: Oral & Written Communication
  • Share platform knowledge, best practices, and methodologies through training, documentation, and cross-team collaboration.
  • Support analytics and automation workflows by enabling access to data, reviewing project requests, and assisting with interpretation.
  • Communicate platform updates, risks, performance, and issue resolutions clearly during meetings and collaborative sessions.
  • Work effectively with leaders, technical peers, and end users, ensuring strong communication across both technical and non-technical stakeholders.

Other Duties
  • Perform additional tasks as assigned to support the AI/ML platform, MLOps practices, and enterprise data science initiatives.

EDUCATION
  • Required: Bachelor's Degree Computer Science, Software Engineering, Data Science, Physics, Math & Statistics, or another related engineering discipline.
  • Preferred: Master's Degree Computer Science, Software Engineering, Data Science, Physics, Math & Statistics, or another related engineering discipline.

WORK EXPERIENCE
  • Required: 3 years in machine learning engineering, data science, data engineering, and/or software engineering experience.
  • Required: 1 year experience with Master's degree.
  • No experience required with PhD.

Preferred Experience/Skills: Healthcare experience needed, experience with MLOps platforms and/or cloud AI certifications, strong proficiency in CI/CD and automation of the AI lifecycle, experience working on healthcare focused machine learning projects. Experience with Azure and/or Kubernetes. Proficiency in services such as Azure Kubernetes Services and Azure ML (or similar).
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
Additional Information
  • Requisition ID: 178799
  • Employment Status: Full-Time
  • Employee Status: Regular
  • Work Week: Days
  • Minimum Salary: US Dollar (USD) 123,000
  • Midpoint Salary: US Dollar (USD) 154,000
  • Maximum Salary : US Dollar (USD) 185,000
  • FLSA: exempt and not eligible for overtime pay
  • Fund Type: Hard
  • Work Location: Remote (within Texas only)
  • Pivotal Position: Yes
  • Referral Bonus Available?: Yes
  • Relocation Assistance Available?: Yes

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