Associate Director, Scientific Computing and AI Engineer

Role: Scientific Computing and AI Engineer leading the design and enhancement of computational infrastructure to accelerate drug discovery and clinical research in neurodegenerative diseases. Responsibilities: architect and optimize GPU clusters, hybrid cloud HPC systems, and storage; collaborate with scientists to profile workloads and improve system performance; design AI/ML and generative AI solutions, including data pipelines, model deployment, MLOps, and emerging capabilities like digital twins; provide technical leadership, set platform standards, mentor engineers, and evaluate technologies; support regulated biotech environments with GxP considerations. Requirements: Bachelor’s/Master’s in Computer Science or related field; 10-12+ years in platform/scientific computing or infrastructure engineering; deep expertise in HPC clusters (Slurm/LSF), cloud platforms, AI/ML deployment, generative AI frameworks (LangChain, AutoGen), and scripting (Python); experience with vector databases, GxP, 21 CFR Part 11; proven end-to-end project leadership in resource-constrained settings. HighValue: neurodegenerative disease research, HPC, cloud scaling, AI/ML platform engineering, generative AI, GxP compliance, biopharma R&D infrastructure. WorkSetup: not specified; likely hybrid or on-premise based on infrastructure scope.