Computational Scientist

Empire AI supports AI-driven research across New York State’s public and private research institutions. The Computational Scientist partners with researchers to build, optimize, and scale computational workflows across disciplines using shared infrastructure for machine learning, simulation, data science, and secure computing.

Responsibilities:

• Work with researchers to build, debug, and tune computational workflows across HPC and AI systems
• Port, profile, and optimize GPU-accelerated applications, parallel codes, and distributed machine learning training pipelines
• Build scalable, reproducible workflows using tools such as Slurm, Dask, Apptainer, Snakemake, or Nextflow
• Contribute hands-on to the technical components of research projects across partner institutions
• Perform data wrangling, model training, and performance benchmarking in collaboration with faculty
• Package research code into reusable software modules, containers, and scalable workflows
• Serve as a go-to technical resource for AI/ML tools, GPU optimization, and data-intensive computing
• Troubleshoot user jobs and work with system administrators to surface user needs and platform issues
• Test and evaluate new software tools and frameworks for readiness, compatibility, and performance
• Write and maintain user documentation, examples, and best-practice guides
• Deliver technical workshops or tutorials for domain scientists adopting advanced computing tools
• Contribute technical sections to grant proposals, publications, white papers, and presentations as needed
• Support students and junior researchers through code reviews, office hours, and one-on-one consultations
• Participate in pilot projects and cross-institutional knowledge-sharing initiatives