Manager, Computational Scientific Programming, Research Computing

Position Summary

The Manager, Computational and Scientific Programming will support AI-driven research across New York State's public and private research institutions. This position serves as a key technical partner to researchers leveraging Empire AI's shared infrastructure for machine learning, simulation, data science, and secure computing.

Duties and 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
• Aid in 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

Minimum Qualifications

• Ph.D. in a STEM discipline involving computational research (e.g., Computer Science, Physics, Bioinformatics, Applied Math, Engineering)
• 5+ years of experience supporting or conducting research using HPC, AI/ML, or large-scale data infrastructure
• Demonstrated ability to support researchers in a collaborative, service-oriented environment
• Proficiency with programming languages such as Python, R, or C/C++
• Experience with Linux environments and job scheduling systems (e.g., Slurm)

Preferred Qualifications

• Advanced knowledge of deep learning frameworks (e.g., PyTorch, TensorFlow) and scientific computing tools (e.g., NumPy, scikit-learn, CUDA, MPI)
• Experience developing scalable workflows for multi-node GPU clusters
• Familiarity with research data lifecycle management, FAIR principles, and secure data handling (e.g., HIPAA, NIST 800-171)
• Experience writing or supporting competitive federal proposals (e.g., NSF, NIH, DOE)
• Background in reproducible research practices, version control (e.g., Git), and containerized computing
• Contributions to open-source scientific software projects or community research tools