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Machine Learning Remote Internship Jobs in Pennsylvania

Data Scientist

Conshohocken, PA · On-site +1

$175K/yr

Remote (Preference for Northeast/Mid-Atlantic; monthly travel to Plymouth Meeting, PA as needed ... Develop predictive models, scoring frameworks, and machine learning solutions that enhance business ...

Research Scientist, Learnable Planner

Pittsburgh, PA · On-site +1

$158K - $269K/yr

  • Medical

  • Dental

  • Vision

  • PTO

Qualifications: - MS/PhD degree in Computer Science, AI, Machine Learning, Computer Vision ... internships, work experience, research projects, and papers at top conferences. - Strong ...

  • Medical

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Quantum Machine Learning and AI: Develop novel quantum algorithms and computational frameworks for ...

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Experiences with machine learning is a plus to the application. * Solid understanding of the ...

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Strong foundation in machine learning concepts, including supervised, unsupervised, and ...

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... The work will involve research on machine learning, digital twins, electronic design automation ...

... interns; foster a culture of scientific rigor and rapid experimentation. - Publish high-impact research at top-tier conferences in machine learning or robotics. Qualifications: - Masters/PhD in ...

Showing results 21-40

Machine Learning Remote Internship information

What is a machine learning remote internship?

A Machine Learning Remote Internship is a temporary, structured work experience where interns contribute to machine learning projects from a remote location, such as their home. Interns typically work with teams on tasks like data preprocessing, building models, and evaluating results, while gaining practical knowledge and mentoring. These internships are ideal for students or recent graduates looking to develop their skills in machine learning, programming, and data science without the need to relocate. They often involve working with Python, popular ML libraries, and real-world datasets. Communication and collaboration are maintained through online tools and regular meetings.

What types of projects can I expect to work on during a machine learning remote internship?

During a remote machine learning internship, you can expect to contribute to projects such as data preprocessing, model development, and performance evaluation. Interns often work on real-world datasets, applying techniques like regression, classification, clustering, or deep learning, depending on the organization's focus. Collaboration with data scientists, engineers, and other interns is common, typically via virtual meetings and shared code repositories. These projects provide hands-on experience and often culminate in presenting your findings to the team, offering valuable exposure to industry-standard workflows and tools.

What are the key skills and qualifications needed to thrive as a machine learning remote intern, and why are they important?

To thrive as a Machine Learning Remote Intern, you need a solid background in programming (especially Python), mathematics/statistics, and a foundational understanding of machine learning concepts, often gained through coursework or relevant projects. Familiarity with machine learning libraries (like TensorFlow, PyTorch, and scikit-learn), version control systems (such as Git), and cloud platforms is typically expected. Strong problem-solving abilities, self-motivation, and effective remote communication set top interns apart. These skills and qualities enable efficient collaboration, successful project delivery, and continuous learning in a dynamic, distributed work environment.

What is the difference between Machine Learning Remote Internship vs Data Science Intern?

AspectMachine Learning Remote InternshipData Science Intern
Required CredentialsBasic programming, math, and machine learning knowledgeStatistics, programming, and data analysis skills
Work EnvironmentRemote, collaborative teams, project-basedRemote or on-site, data analysis and modeling tasks
Industry UsageTech, AI, startups, research labsTech, finance, healthcare, consulting
Search & Comparison IntentUnderstanding internship roles in MLExploring data science internship opportunities

Machine Learning Remote Internships focus on developing models and algorithms, often requiring knowledge of programming and math. Data Science Internships involve analyzing data, creating reports, and supporting decision-making. While both roles are remote and industry-relevant, ML internships emphasize algorithm development, whereas data science roles focus on data analysis and visualization.

What cities in Pennsylvania are hiring for Machine Learning Remote Internship jobs?

Cities in Pennsylvania with the most Machine Learning Remote Internship job openings:

Infographic showing various Machine Learning Remote Internship job openings in Pennsylvania as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 26% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Huck Institutes of the Life Sciences NSF NCEMS Postdoctoral Scholar

The Pennsylvania State University

University Park, PA • On-site, Remote

Full-time

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


Job description

APPLICATION INSTRUCTIONS:
  • CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process. Please do not apply here, apply internally through Workday.
  • CURRENT PENN STATE STUDENT (not employed previously at the university) and seeking employment with Penn State, please login to Workday to complete the student application process. Please do not apply here, apply internally through Workday.
  • If you are NOT a current employee or student, please click "Apply" and complete the application process for external applicants.

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional information on remote work at Penn State, seeNotice to Out of State Applicants.

This is a term position; length of the term will be discussed during the interview process. Continuation past the termlengthdiscussed willbebasedonuniversityneed,performance,and/oravailabilityoffunding.

POSITION SPECIFICS

Postdoctoral Scholar (Machine Learning or Artificial Intelligence in Molecular and Cellular Biology)

The National Synthesis Center for Emergence in the Molecular and Cellular Sciences (NCEMS) at Penn State University (ncems.psu.edu) seeks an outstanding scientist to fill a Postdoctoral Scholar position in Machine Learning or Artificial Intelligence housed within the Huck Institutes of Life Sciences at Penn State University.

NCEMS is an NSF-funded interdisciplinary research center positioned at the interface of data science, molecular and cellular biology, and quantitative physical sciences. The Center provides leadership in the integration of diverse, publicly available datasets to gain insights into emergent phenomena in molecular and cellular biology.

About the Position

The successful candidate, in collaboration with faculty and research staff at NCEMS, will conduct original research applying machine learning, artificial intelligence, computer science, statistical learning, or related computational approaches to problems in molecular and cellular biology. Research may involve large-scale public datasets, biological data harmonization, representation learning, predictive modeling, foundation models, network analysis, graph-based learning, uncertainty quantification, scientific machine learning, or interpretable AI.

This position is full time, on-site at the Penn State University Park campus. This position does not permit remote work. This is a term appointment funded for one year from the date of hire, with an excellent chance for renewal based upon mutual agreement.

Requirements

A PhD in Computer Science, Data Science or a closely related field is required. The successful candidate will have a strong foundation in machine learning, artificial intelligence, statistical learning, scientific computing, data science, or related computational approaches. Candidates must have experience developing or implementing machine learning methods for large-scale data analysis, predictive modeling, or biological discovery. Expertise in Python is expected. A demonstrated ability to conduct research and produce scholarly outputs, as evidenced by publications in peer-reviewed journals. Familiarity with molecular and cellular biology concepts is also desirable. Candidates must be independent self-starters, have a strong work ethic, strong interpersonal and written communication skills, and the ability to work well in a collaborative team environment.

Application Process

Applications must be submitted electronically in a single PDF and should include:

  • A cover letter
  • Curriculum vitae (CV)

BACKGROUND CHECKS/CLEARANCES

Employment with the University will require successful completion of background check(s) in accordance with University policies.

BENEFITS

Penn State provides a competitive benefits package for full-time employees designed to support both personal and professional well-being.

For more detailed information, please visit ourBenefits Page. (Note: For Postdoctoral benefits, please see our Postdoctoral Benefits page.)

CAMPUS SECURITY CRIME STATISTICS

Pursuant to the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act and the Pennsylvania Act of 1988, Penn State publishes a combined Annual Security and Annual Fire Safety Report (ASR). The ASR includes crime statistics and institutional policies concerning campus security, such as those concerning alcohol and drug use, crime prevention, the reporting of crimes, sexual assault, and other matters. The ASR is available for review here.

EEO IS THE LAW

Penn State is an equal opportunity employer and is committed to providing employment opportunities to all qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. If you are unable to use our online application process due to an impairment or disability, please contact 814-865-1473.

Penn State is committed to and accountable for advancing equity, respect, and belonging. We embrace individual uniqueness, as well as a culture of belonging that supports equity initiatives, leverages the educational and institutional benefits of inclusion in society, and provides opportunities for engagement intended to help all members of the community thrive. We value belonging as a core strength and an essential element of the university's teaching, research, and service mission.

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About Pennsylvania State University

Sourced by ZipRecruiter

Pennsylvania State University, often referred to as Penn State, is a major, public, research-intensive university located in University Park, PA, US. This esteemed institution serves as an important player within the education industry, offering a plethora of academic programs across various disciplines. The university was founded in 1855 with the mission to provide quality education, advanced research, and service to society. Penn State holds firmly to values of integrity, respect, and excellence, fostering a diverse and inclusive community. The university is renowned for its research productivity and its high-ranking programs in areas like engineering, business, and education. One notable achievement of the institution is its designation as a "R1: Doctoral Universities – Very high research activity," demonstrating its commitment to scholarship and discovery.

Industry

Education

Company size

11 - 50 Employees

Headquarters location

University Park, PA, US

Year founded

1855

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