Machine Learning Research Engineer - Mellon College of Science - Pittsburgh Supercomputing Center

Carnegie Mellon University•Pittsburgh, PA

2d•Onsite

About The Position

The Mellon College of Science (MCS) at Carnegie Mellon University, specifically its Pittsburgh Supercomputing Center (PSC), is seeking a Machine Learning Research Engineer to join the Artificial Intelligence and Big Data (AI&BD) Group. This role involves supporting and advancing research, assisting users, and developing and delivering advanced training. The position offers a unique opportunity to collaborate with leading researchers, contribute to significant scientific applications, and advance cutting-edge computing technologies. Responsibilities will be tailored to active project needs.

Requirements

Master’s degree in Computer Science, Machine Learning, Data Science, Engineering, or a related field is required (equivalent experience may be considered).
Minimum 3 years of experience applying ML or high-performance data analytics to real-world problems; graduate education may be considered in lieu of equivalent industry experience.
Strong programming skills in Python and experience with package management.
Proficiency with Linux environments, including shell scripting and software compilation.
Familiarity with at least one web development stack (e.g., Flask, Django, or React-based frontends).
Experience supporting or developing applied machine learning or data analytics solutions.
Excellent communication, teamwork, and creative problem-solving abilities.
A combination of education and relevant experience from which comparable knowledge is demonstrated may be considered.
Successful background check.

Nice To Haves

Ph.D. in a relevant discipline is strongly preferred, especially with demonstrated research or applied experience in AI, machine learning, or data-driven science.
Advanced experience with machine learning and statistical libraries (e.g., NumPy, SciPy, Pandas, R, MATLAB).
Hands-on experience with modern AI frameworks such as PyTorch, TensorFlow, or JAX.
Familiarity with containerized environments (e.g., Docker, Singularity) and job schedulers (e.g., Slurm).
A track record of successful research or real-world ML deployments beyond coursework.

Responsibilities

Collaborate with academic and industry partners to develop AI and data-driven solutions using advanced HPC infrastructure.
Provide technical support for domain-specific projects with academic and private-sector researchers to develop and test prototype solutions applying high performance computing capabilities to data science challenges.
Support the deployment and optimization of AI software on PSC’s production and experimental systems.
Assist in the development of best practices for scalable AI, including benchmarking and comparative evaluation of various software frameworks and advanced hardware platforms.
Support the development of advanced training content for briefings, seminars, workshops, and tutorials, and assist with its delivery.
Install, test, and deploy AI and data analytics software on PSC’s production and research platforms.
Provide advanced user support on topics involving AI, big data, and data analytics software and hardware environments.
Lead or support the dissemination of results through white papers, presentations at conferences and/or journal publications.
Contribute to grant proposals and related efforts to attract funding.
Execute runtime analysis and implement improvements of existing machine learning environments.
Develop, implement, and maintain tools for continuous testing and for efficient high performance resource job scheduling.
Actively discuss and implement new ideas in close collaboration with other members of the Artificial Intelligence and Big Data Group and other groups across the center.
Help design and maintain group web pages to showcase research projects and resources.