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Remote Machine Learning Jobs in State College, PA

Remote Machine Learning information

See State College, PA salary details

$24.9K

$41.6K

$86.1K

How much do remote machine learning jobs pay per year?

As of Jul 2, 2026, the average yearly pay for remote machine learning in State College, PA is $41,647.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,800.00 and $45,000.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and often working at large tech companies or in specialized industries can earn salaries approaching or exceeding $500,000 annually. Compensation may include base salary, bonuses, and stock options, especially in high-demand markets.

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Engineer, and why are they important?

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

How to make 2000 a week working from home?

Remote machine learning professionals can earn $2,000 or more weekly by taking on high-paying freelance projects, consulting roles, or working for companies that offer remote positions with competitive salaries. Building specialized skills in programming, data analysis, and tools like Python, TensorFlow, or cloud platforms can increase earning potential. Consistent work, a strong portfolio, and networking are key to reaching this income level from home.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a Machine Learning Engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is the difference between Remote Machine Learning vs Data Scientist?

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Are there remote machine learning jobs?

Yes, remote machine learning jobs are widely available across various industries, often requiring skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch. Many companies offer flexible schedules and remote work options for qualified candidates, especially in tech and research sectors.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role involves understanding algorithms, data preprocessing, and model optimization. While AI automation tools can handle certain tasks, MLEs are essential for creating, fine-tuning, and maintaining complex AI systems, making complete replacement unlikely in the near term.
What are the most commonly searched types of Machine Learning jobs in State College, PA? The most popular types of Machine Learning jobs in State College, PA are:
What job categories do people searching Remote Machine Learning jobs in State College, PA look for? The top searched job categories for Remote Machine Learning jobs in State College, PA are:
What cities near State College, PA are hiring for Remote Machine Learning jobs? Cities near State College, PA with the most Remote Machine Learning job openings:
Postdoctoral Scholar

Postdoctoral Scholar

Penn State University

University Park, PA • On-site, Remote

Full-time

Posted 25 days ago


Penn State University rating

7.8

Company rating: 7.8 out of 10

Based on 103 frontline employees who took The Breakroom Quiz

197th of 544 rated colleges and universities


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, see Notice to Out of State Applicants.
This is a term position; length of the term will be discussed during the interview process. Continuation past the term length discussed will be based on university need, performance, and/or availability of funding.
POSITION SPECIFICS
The College of EMS - Energy Institute at Penn State invites applications for an immediate position of Postdoctoral Scholar to conduct research on projects in collaboration with Dr. Sanjay Srinivasan, who directs the Penn State Initiative for Geostatistics and Geo-Modeling Applications (PSIGGMA).
This initiative currently supports a group of 5 researchers working on topics such as the application of reinforcement learning for optimum reservoir development, the application of machine learning and multipoint geostatistics for characterization of fractures and novel algorithms for the integration of time-lapse seismic data into models for CO2 plume movement during sequestration.
These projects are supported through grants from NSF, DOE and the John and Willie Leone Family Endowment.
Applications are sought from researchers working in the areas of advanced data analytics and machine learning applied to solve subsurface reservoir characterization and modeling related challenges. Specifically, expertise looking at geochemical, geomechanical, and hydrologic data sets, high-performance modeling capabilities and the development of a suite of AI technologies, including surrogate models, physics-informed machine learning, and digital twins to enhance engineering evaluation and control of the subsurface during characterization, drilling,
stimulation, and/or production will be preferred
Applicants must hold an advanced degree, Ph.D. or equivalent in petroleum/subsurface engineering, geophysics, AI/ML, geostatistics or related field by hire date.
Strong background and training in reservoir characterization techniques and/or subsurface process modeling especially using advanced data analytics and machine learning approaches is required.
Candidates should possess excellent written and verbal communication skills, be able to work independently and have excellent computer skills. Clear demonstration of computer coding skills and use of data analysis software is desirable.
Interested candidates should submit the following:
  • An application letter highlighting qualifications for the position
  • A curriculum vitae including educational background, employment history, and a list of peer reviewed publications
  • Research statement of your interests in the context of desired qualifications
  • Contact information for three references.

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 our Benefits 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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