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Remote Nvidia Deep Learning Jobs in Pennsylvania

The Pennsylvania State University

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Preferred Experience with one or more of the following is strongly preferred: deep learning for ...

The Pennsylvania State University

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Experience with one or more of the following is strongly preferred: deep learning for image ...

The Pennsylvania State University

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Preferred Experience with one or more of the following is strongly preferred: deep learning for ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

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Remote Nvidia Deep Learning information

What is the difference between Remote Nvidia Deep Learning vs Remote Machine Learning Engineer?

AspectRemote Nvidia Deep LearningRemote Machine Learning Engineer
Required CredentialsDeep learning certifications, Nvidia GPU expertise, programming skills in Python and CUDAMachine learning certifications, Python, data analysis, model deployment skills
Work EnvironmentRemote, GPU-intensive tasks, AI research, model trainingRemote, data processing, model development, deployment
Industry UsageAI research labs, tech companies, autonomous vehiclesTech firms, finance, healthcare, e-commerce

Remote Nvidia Deep Learning focuses on developing AI models using Nvidia GPUs and CUDA, often in research or AI-specific roles. Remote Machine Learning Engineers work on building and deploying machine learning models across various industries. While both roles require programming and data skills, Nvidia Deep Learning emphasizes GPU expertise and AI research, whereas Machine Learning Engineers focus on broader model deployment and application.

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For Remote Nvidia Deep Learning jobs in Pennsylvania, the most frequently searched job titles are:

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Remote Nvidia Deep Learning jobs near you
Infographic showing various Remote Nvidia Deep Learning job openings in Pennsylvania as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 75% Full Time, 21% Part Time, and 2% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution.

Postdoctoral Scholar - Reinhart Group - Materials Science and Engineering

On-site, Remote

The Pennsylvania State University
Education • 11 - 50 employees
Learn more about The Pennsylvania State Universityexternal

Full-time

Re-posted 22 hours ago

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

The Department of Materials Science and Engineering in the College of Earth and Mineral Sciences is searching for a postdoctoral scholar. The position will involve machine learning for autonomous thin-film materials synthesis, including representation learning for scientific data, multimodal data fusion, and real-time predictive modeling. This work will be performed as part of LATTICE (Layered and Thin Film Technologies with Intelligent Cloud Experimentation), a National Science Foundation Programmable Cloud Laboratory at the Pennsylvania State University's University Park campus.

The postdoctoral scholar will develop specialized machine learning models that enable AI systems to interpret scientific data from instruments including atomic force microscopy, reflection high-energy electron diffraction, spectroscopic ellipsometry, X-ray diffraction, and similar characterization methods. These models serve as the perceptual layer for a multi-agent AI framework that will guide autonomous materials synthesis and interact with robotic systems. The models will be trained, calibrated, and validated against the specific data modalities produced by LATTICE instrumentation. The scholar will deploy these models on edge-computing infrastructure for real-time feedback during deposition and integrate them with the Lifetime Sample Tracking data platform. The position requires close collaboration with LATTICE domain scientists in thin-film growth and characterization, AI researchers developing the agentic workflow framework, and future users of the LATTICE framework.

Requirements

Candidates must have a Ph.D. in Materials Science and Engineering, Computer Science, Electrical Engineering, Physics, or a related field, plus a strong record of research experience in applied machine learning, computer vision, and/or scientific data analysis.

Preferred

Experience with one or more of the following is strongly preferred: deep learning for image analysis, multimodal or multi-task learning, or deployment of ML models in real-time or edge-computing environments. Domain knowledge of materials science, chemistry, or physics will be an advantage. Extensive programming experience in Python is required, and familiarity with PyTorch or JAX is preferred.

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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