The Mellon College of Science (MCS) is home to four departments and many programs and research centers that cross disciplines. We approach scientific problems from fresh angles using creative interdisciplinary approaches while drawing on our departmental strengths in the core sciences.

Our Pittsburgh Supercomputing Center (PSC) within MCS is seeking a Machine Learning Research Engineer. In this role, you will work within the PSC’s Artificial Intelligence and Big Data (AI&BD) Group to support and advance research, assist with user support, as well as develop and deliver advanced training.  This position offers an exciting opportunity to collaborate with top researchers, contribute to impactful scientific applications, and help advance cutting-edge computing technologies.

Responsibilities are determined by active project needs. Some examples are as follows:

• Collaborate with academic and industry partners to develop AI and data-driven solutions using advanced HPC infrastructure.
• Technically support 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 elements of benchmarking and comparative evaluation involving 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 as needed 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.

Adaptability, excellence, and passion are vital qualities within Carnegie Mellon University.  We are in search of a team member who can effectively interact with a varied population of internal and external partners at a high level of integrity. We are looking for someone who shares our values and who will support the mission of the university through their work.

• Master’s degree in Computer Science, Machine Learning, Data Science, Engineering, or a related field is required (equivalent experience may be considered).
• Ph.D. in a relevant discipline is strongly preferred, especially with demonstrated research or applied experience in AI, machine learning, or data-driven science.
• 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.

Preferred Qualifications

• 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.

Requirements:

• Successful background check

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