Team Lead, AI Scientific Support

Team Lead, AI Scientific Support

Empire AI is establishing New York as the national leader in responsible artificial intelligence. Backed by a consortium of top academic and research institutions including Columbia, Cornell, NYU, CUNY, RPI, SUNY, Rochester Schools, Mount Sinai, Simons Foundation, and the Flatiron Institute.

By leveraging the state’s rich academic resources and research institutions, Empire AI is driving innovation in fields like medicine, education, energy, and climate change, all while giving New York’s researchers access to computing resources that are often prohibitively expensive and only available to big tech companies, fueling statewide innovation, driving economic growth, and preparing a future-ready AI workforce to tackle society’s most complex challenges.

The initiative is funded by $500 million in public and private investments, State Capital Grant, Academic Institutions, Simons Foundation, Flatiron Institute, and Tom Secunda (Co-Founder of Bloomberg).

Position Summary

The Team Lead, AI Scientific Support plays a critical role in helping faculty, researchers, and students translate scientific ambition into real-world impact through Empire AI’s shared advanced computing platforms.

Reporting to the Director, AI Research Computing, the Team Lead, AI Scientific Support oversees day-to-day support operations, leads a team of technical support staff, and serves as a hands-on expert in high-performance computing (HPC), AI workflows, and data-intensive science. This role balances user advocacy with infrastructure insight—ensuring every Empire AI user has the tools, knowledge, and guidance to succeed on the platform.

Duties and Responsibilities

• Manage daily operations of the user support team, including workload coordination, scheduling, and performance tracking
• Mentor, train, and guide technical staff to deliver exceptional service to Empire AI users
• Provide escalation support for complex user issues involving HPC systems, AI tools, secure enclaves, and distributed storage
• Ensure a responsive, solutions-oriented support model across institutions and user communities
• Serve as the first point of contact for new users, supporting account provisioning, environment configuration, and system orientation
• Help users understand system architecture, policies (e.g., storage quotas, job scheduling), and available software environments
• Support secure computing onboarding, including training on compliance frameworks and protected data workflows
• Diagnose and resolve user-reported issues related to software environments, job performance, and access
• Monitor consulting queues and ticketing systems to maintain fast, effective support response times
• Collaborate with systems administrators and developers to resolve platform-side incidents and ensure system uptime
• Develop and maintain in-depth knowledge of Empire AI infrastructure, user tools, and HPC best practices
• Create and maintain user-facing documentation, quick-start guides, and troubleshooting resources
• Lead technical training sessions and workshops tailored to different user skill levels and scientific domains
• Contribute to Empire AI user community events, forums, and collaboration platforms
• Promote inclusive access to Empire AI systems, including engagement with underrepresented communities in AI research
• Identify and implement improvements to user support workflows and service operations
• Participate in pilots, infrastructure rollouts, or tool evaluations to assess and expand Empire AI’s service capabilities
• Contribute to grant development by assisting researchers with computational resource estimates and data management planning
• Track usage patterns and generate insights to enhance user experience, training materials, and system support strategy

Minimum Qualifications

• Bachelor’s degree in a STEM discipline (e.g., Computer Science, Physics, Engineering, Data Science)
• At least 18 months of experience using or supporting high-performance or research computing systems
• Strong communication and problem-solving skills, with the ability to work effectively with diverse users
• Experience with Linux/Unix systems, job schedulers (e.g., Slurm), and scientific software environments
• Scripting experience (e.g., Bash, Python, or similar)

Preferred Qualifications

• Master’s degree in a scientific or technical field, or equivalent experience in a research computing support role
• Familiarity with machine learning workflows, AI research tools (e.g., PyTorch, TensorFlow), or scientific simulation environments
• Experience working with faculty or research groups in academic, national lab, or industry research settings
• Exposure to secure or regulated research environments (e.g., HIPAA, NIST 800-171)
• Experience with containers (Apptainer/Singularity, Docker) and version control systems (e.g., Git)
• Background in delivering user training, workshops, or documentation

Compensation

Our compensation reflects the cost of labor across several US geographic markets. The base pay and target total cash for this position range from $100,000 to $200,000. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience.