Artificial Intelligence/Machine Learning Data Science Engineer

Pennsylvania State University
State College, PA, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$81,312.0 - $122,016.0
Working hours
Regular working hours

Tech stack

Artificial Intelligence Software Applications Big Data Bioinformatics C++ (Programming Language) Cloud Computing Computer Clusters Computational Biology Data Systems Software Debugging R (Programming Language) Python (Programming Language)
+15 more
MATLAB Machine Learning Program Design Languages Power BI Tensorflow Scientific Computating Software Engineering SQL Databases AI Infrastructure Reinforcement Learning High Performance Computing Large Language Models Deep Learning Generative AI Information Technology

Job description

The Institute for Computational and Data Sciences (ICDS) at Penn State is seeking an Artificial Intelligence/Machine Learning Data Science Engineer to join our Research Innovations with Scientists and Engineers (RISE) team.

ICDS works with researchers from more than 70 academic departments from nearly all of Penn State’s academic colleges and campuses, facilitating new collaborations, funding new areas of research, collaborating to overcome computational and data science challenges, building a diverse community of scholars, and providing a robust supercomputer for the Penn State community, called Roar. ICDS seeks to equip researchers with the most cutting-edge computing tools and resources to further their science, and as a part of ICDS, you will be contributing to this goal.

The position will report to the RISE Team Manager.

Work Arrangement: This position requires on-site work at University Park and is not supportive of remote work.

As the RISE AI/ML Engineer, your responsibilities include the following:

  • Provide technical expertise to university constituents in research, specification, design, development, and implementation of AI/ML/DL solutions, combining disciplinary knowledge and technical expertise.

  • RISE AI/ML Engineers use their skills in machine learning, deep learning, AI, big data and software application and development to provide these skills to assist researchers in developing solutions for their research projects and grants.

  • Using a software engineering approach, our AI/ML engineer will formulate and define scope and objectives and detailed specifications for assigned projects; provide guidance or develop program design, coding, testing, debugging, and documentation; advance researchers’ goals by providing or enabling scientific data solutions through technical consulting.

Requirements

  • Applicants must demonstrate knowledge of Linux-based computing, high-performance computing, GPU-enabled environments, distributed or cluster-based systems, and AI infrastructure, along with experience developing or supporting computational platforms, research software, or technical workflows.

  • Candidates should have professional or research experience applying artificial intelligence, machine learning, deep learning, large language models, predictive analytics, or related methods, including application development in Python and experience with modern AI/ML frameworks such as TensorFlow.

  • The successful candidate will be able to develop, implement, test, troubleshoot, and optimize AI/ML solutions; automate analytical workflows; investigate complex computational or system issues; work productively with interdisciplinary researchers; and communicate technical information clearly through documentation, consultation, presentations, and user training.

Desired skills and experience include the following:

  • Experience applying AI, machine learning, statistical modeling, or predictive analytics in health research, healthcare operations, biomedical data, or other applied research settings is desirable.
  • Experience operating, maintaining, upgrading, validating, benchmarking, or optimizing GPU clusters and other AI research infrastructure; working with AI systems; collaborating with hardware, software, cloud, or systems vendors; and establishing deployment, testing, validation, security, or performance-monitoring procedures.
  • Experience with large language models, generative AI, multimodal models, AI agents, reinforcement learning, optimization-based machine learning, scientific computing, SQL, R, MATLAB, C/C++, Power BI, or related tools is welcome.
  • Candidates who have developed technical documentation, delivered workshops or training, supported researchers directly, or contributed to reproducible and reliable research software are especially encouraged to apply.

Preferred Education:

  • A PhD in Machine Learning, Computational Biology, Bioinformatics, Computer Science, Statistics, Data Science, or a related field is preferred.

Candidates must also have impeccable ethics and integrity with a strong work ethic as well as strong interpersonal and written skills and the ability to work well in a team environment., Bachelor’s Degree 1+ years of relevant experience; or an equivalent combination of education and experience accepted Required Certifications: None

BACKGROUND CHECKS/CLEARANCES Employment with the University will require successful completion of background check(s) in accordance with University policies. Penn State does not sponsor or take over sponsorship of a staff employment Visa. Applicants must be authorized to work in the U.S.

Benefits & conditions

The salary range for this position, including all possible grades, is $81,312.00 - $122,016.00.

Salary Structure - Information on Penn State’s salary structure

Penn State provides a competitive benefits package for full-time employees designed to support both personal and professional well-being. In addition to comprehensive medical, dental, and vision coverage, employees enjoy robust retirement plans and substantial paid time off which includes holidays, vacation and sick time. One of the standout benefits is the generous 75% tuition discount, available to employees as well as eligible spouses and children. For more detailed information, please visit our Benefits Page.

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