Manager, Computational and Scientific Programming, Research Computing

Empire AI is establishing New York as the national leader in responsible artificial intelligence. The Manager, Computational and Scientific Programming will support AI-driven research across New York State’s public and private research institutions by collaborating with researchers to design, optimize, and scale computational workflows.

Responsibilities:

• Collaborate with researchers to design, implement, and tune computational workflows across HPC and AI systems
• Support GPU-accelerated applications, parallel computing, and distributed machine learning training pipelines
• Enable scalable, reproducible workflows using tools such as Slurm, Dask, Apptainer, Snakemake, or Nextflow
• Partner with research teams across institutions to co-develop technical components of research projects
• Act as a technical co-PI or collaborator on funded projects, contributing to research design and implementation
• Assist with data wrangling, model training, and performance benchmarking in collaboration with faculty
• Contribute to the preparation of grant proposals by drafting technical narratives, budget justifications, and cyberinfrastructure plans
• Co-author or support preparation of publications, white papers, and presentations
• Help translate research outputs into reusable software modules or scalable workflows
• Provide subject matter expertise in AI/ML tools, GPU optimization, and data-intensive computing
• Work with system administrators and architects to identify user needs and ensure platform alignment
• Evaluate new software tools and frameworks for readiness, compatibility, and performance
• Provide informal mentoring to junior researchers, postdocs, and students working on computational projects
• Deliver technical workshops or tutorials for domain scientists adopting advanced computing tools
• Contribute to cross-institutional knowledge-sharing and training initiatives
• Participate in strategic infrastructure planning or pilot projects
• Contribute to institutional initiatives in responsible AI, compliance, or interdisciplinary data science